Role directory

Python jobs

25 active, referral-verified opportunities.

Code / Remote

CUDA Engineering Expert

1. Role Overview — Mercor is seeking GPU kernel optimization experts to contribute to a project with a leading AI lab. This opportunity is designed for freelancers with strong C++ skills, practical GPU programming experience, and the ability to improve kernel performance using profiler-guided analysis. You’ll help evaluate, optimize, and reason about GPU kernels across modern hardware environments. This is a contract-based opportunity for specialists who enjoy squeezing performance out of modern GPU architectures. — 2. Key Responsibilities • Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization • Use profiler metrics such as L2 cache hit rate, L2 throughput, occupancy, and related signals to guide kernel improvements • Review GPU kernel implementations and identify bottlenecks without requiring extensive background in the underlying algorithms • Write, modify, and reason about C++17, Python, and GPU programming code • Apply CUDA, HIP, shader programming, or related kernel programming expertise to improve performance outcomes • Document optimization decisions clearly, including when specific profiler metrics are or are not useful — 3. Ideal Qualifications • Available to work at least 20 hrs/wk • Fluent in core C++ features through C++17 • Working knowledge of Python and Git • Fluent in at least one GPU programming model, such as CUDA, HIP, Slang, HLSL, GLSL, or related kernel programming • At least 1 year of professional or graduate-level research experience working with GPUs • Strong understanding of GPU profiler performance metrics and how to use them to optimize kernels • Ability to optimize GPU kernels without needing deep prior context on every algorithm • Experience with CUDA, HIP, CUDA C++ Core Libraries, inline PTX assembly, or tensor core-level optimization is a plus • Experience optimizing kernels for NVIDIA Blackwell hardware is a plus • Familiarity with NSight Compute is a plus • Prior experience with GPU hardware organizations such as NVIDIA, AMD, or Qualcomm is a plus • Open-source contributions related to GPU kernel optimization are a plus — 4. Application Process • Submit your resume or relevant technical background to get started • Qualified applicants may be asked to complete a brief technical assessment or submit additional information

$500 / per-taskOpen / Referral verified
Math / Remote

Data Science Expert

1. Role Overview — Mercor is partnering with a leading AI research organization to engage experienced data scientists for a project focused on evaluating how well AI systems perform real-world data science work. Rather than producing deliverables yourself, you will define what excellent work looks like: designing task-specific grading criteria and scoring completed work samples with rigorous, well-reasoned written justifications. — 2. Key Responsibilities • Design precise, task-specific grading criteria for real-world data science deliverables (analyses, models, dashboards, experiment readouts, and written recommendations) • Score AI-generated and human work samples against those criteria, with detailed written justifications for every score • Apply consistent, evidence-based judgment so that scores are reproducible and defensible • Incorporate structured feedback from senior reviewers and iterate quickly on your work — 3. Ideal Qualifications • 5+ years of professional data science experience in industry • Background in business operations, product, or growth data science at top-tier technology companies • Deep fluency in experiment design and A/B testing, metric definition, SQL/Python analysis, and communicating findings to executive stakeholders • Exceptionally strong written communication • Detail-oriented, consistent, and comfortable having your judgment reviewed and calibrated against peers • Prior experience with AI training, evaluation, or human-data projects is a strong plus — 4. Application Process • Submit your resume or relevant technical background to get started • Qualified applicants may be asked to complete a brief technical assessment or submit additional information

$120 - $170 / hourOpen / Referral verified
Code / Remote

Data Scientist Talent Network

Mercor is building a network of experienced data scientists for potential future projects with leading AI research organizations. These projects may focus on evaluating how effectively AI systems perform real-world data science work. — There is no immediate project opening, but qualified applicants may be contacted as relevant opportunities become available. — 2. Potential Responsibilities — Future projects may involve: • Designing precise, task-specific grading criteria for data science deliverables, including exploratory data analyses, statistical modeling work, machine learning pipelines, experimentation and A/B test write-ups, feature engineering, and technical reports or notebooks • Evaluating AI-generated or human-created work against established criteria • Providing detailed written justifications for evaluations and scores • Applying consistent, evidence-based judgment so that assessments are reproducible and defensible • Incorporating structured feedback from senior reviewers and iterating on submitted work — Specific responsibilities will vary depending on the project. — 3. Ideal Qualifications • 1+ years of professional data science experience • Experience at a leading technology, research, or quantitative firm (such as top FAANG, AI labs, top-tier quant funds, or equivalent) • Strong command of Python, SQL, statistical modeling, machine learning, experimentation and causal inference, and translating messy real-world data into rigorous analyses • Exceptional written communication skills, including the ability to convey technical findings clearly • A detail-oriented and consistent approach to evaluating complex work • Comfort receiving feedback and calibrating judgment against established standards

$100 - $150 / hourOpen / Referral verified
STEM / Remote

Research Physics Expert

Role Overview — We are seeking expert physics researchers to author and verify golden reference solutions for the CritPt benchmark (arXiv:2509.26574v3) — a frontier research-level physics benchmark. Participants will solve CritPt research-level problems end-to-end, audit solutions from other experts, or adjudicate between parallel solution attempts, producing 100%-human-verified reference data used to evaluate large language models on frontier physics reasoning. — Physics Subdomains Covered — High Energy Physics & Mathematical Physics, Biophysics & Statistical Physics, Condensed Matter & AMO, Gravitation / Cosmology / Astrophysics, Quantum Information, Optical Properties of Materials, Magnetic Materials, Measurements in QM. — Key Responsibilities • Solve research-level physics challenges end-to-end with verifiable derivations, code, and peer-reviewed references • Decompose challenges into standalone checkpoint sub-problems that require genuine physical reasoning • Author Python answer templates with auto-grading functions for symbolic or numerical answers • Audit submitted solutions for correctness, scope, and method soundness; deliver actionable feedback across iterations • Adjudicate between parallel solver attempts and decide which solution becomes the golden reference • Document chain-of-thought reasoning, error tolerances, equivalent symbolic forms, and verification test cases — Ideal Qualifications • Solver: PhD or postdoc in the relevant subfield (senior PhD student minimum) • Auditor: Postdoc or junior professor in the relevant subfield (PhD minimum) • Adjudicator: Full professor or industry research PI in the relevant subfield (senior postdoc or junior professor minimum) • Hands-on familiarity with at least two canonical methods of the target subfield, demonstrable through publications (broader coverage strongly preferred) • 3–5 representative publications (arXiv ID or DOI), ideally within the last ~5 years and in the target subfield • Working proficiency with LaTeX, Python, Jupyter, and SymPy • Strong written English (B2/C1/C2 minimum; native or near-native preferred) — More About the Opportunity • Expected commitment: ~10 hours/week, sustained across an 8–10 week window per task pool • Pay range: $80–$135 per hour, based on role and demonstrated expertise • Asynchronous work

$80 - $135 / hourOpen / Referral verified
Code / United States Remote

Senior Software Engineer, Full Stack (Python, Java, Rust, C#, C++)

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models. — 1. Overview — Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're seeking talented Senior Full-Stack Software Engineers with deep, hands-on production expertise across modern application stacks — Python, Java, Rust, C#, C++, and TypeScript — to build, integrate, and stress-test real software on top of frontier models before they ship. Engineers work directly with the AI lab's engineering manager on fast-moving projects and are expected to onboard quickly and contribute working code early. This is a full-time commitment of 40 hours per week. — This is a W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI Lab as part of their extended workforce. — 2. Key Responsibilities • Build and ship full-stack applications, services, and internal tools — in Python, Java, Rust, C#, C++, or TypeScript — that exercise frontier model capabilities end to end. • Integrate pre-release model APIs into working software, including the surrounding scaffolding: tool interfaces, evaluation harnesses, and telemetry. • Diagnose and document model and integration failure modes surfaced while building, translating engineering observations into clear written feedback for the research team. • Prototype quickly against shifting requirements, delivering working increments with limited up-front specification. • Collaborate with the engineering manager and other engineers to maintain consistency in code quality, architecture, and technical documentation. — 3. Core Qualifications • 6+ years of dedicated professional experience building and shipping production software at a recognized, top-tier organization, including ownership of systems end to end. • Deep production experience in at least one of Python, Java, Rust, C#, or C++, plus demonstrated delivery in a second language across a different ecosystem — this cohort is intentionally staffed across multiple language ecosystems. • Hands-on ownership across the stack: backend service and API design, a modern front-end framework (React or equivalent), data modelling, and cloud deployment and operations. • Demonstrated ability to onboard onto an unfamiliar codebase and deliver working code quickly with minimal ramp-up. • Demonstrable career progression. • Ability to engage reliably for at least 40 hours/week during weekdays. • Strong written communication skills and the ability to explain complex technical decisions clearly. — About Cincinnatus LLC: Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. — Equal Employment Opportunity: Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic.

$90 - $110 / hourOpen / Referral verified
Code / United States Remote

Performance Engineer (C++, Python, Rust)

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models. — 1. Overview — We're seeking talented Performance Engineers with deep expertise in low-level systems optimization — specifically C++, Python, and Rust — to bring hands-on technical excellence and elevate the quality of our AI training and inference infrastructure data. This role involves AI model training and evaluation work, including writing and assessing performance-engineering tasks and solutions to generate high-quality training data for frontier AI systems. — This is a W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI Lab as part of their extended workforce. This is a 40-hour full-time engagement, with no conflicts/no other engagements. — 2. Key Responsibilities • Guide research and engineering teams to close knowledge gaps and improve AI model performance in systems-level optimization, compiler engineering, and runtime performance topics. • Design challenging, domain-relevant tasks across multiple specializations, and write accurate and well-structured solutions to performance engineering problems. • Evaluate performance engineering tasks and solutions and provide clear, written technical feedback. • Develop guidelines and detailed rubrics/evaluation frameworks to assess systems design quality across AI workloads. • Collaborate with other subject matter experts to ensure consistency and accuracy in training data. — 3. Core Qualifications • 2+ years of dedicated professional experience in performance engineering, systems programming, or low-level optimization. • Deep hands-on expertise in at least one of the following: C++, Python, or Rust — with working familiarity across the others being a strong plus. • Demonstrable track record of measurable performance improvements on production systems (e.g., latency reduction, throughput gains, memory footprint optimization). • Demonstrable career progression. • Ability to engage reliably for at least 40 hours/week during weekdays. • Strong written communication skills and the ability to explain complex technical decisions clearly. — About Cincinnatus LLC: Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. — Equal Employment Opportunity: Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic.

$70 - $110 / hourOpen / Referral verified
STEM / Remote

Computational Chemistry & Electronic Structure Expert

Computational Chemistry & Electronic Structure Expert — About the Project — We're building a large-scale benchmark to test how well advanced AI systems can solve hard scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data. — This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right. — What You'll Do — You'll create problems that require skilled use of specialized scientific software. Some will ask the AI to compute exact answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently. — Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty. — Domains & Tools We're Hiring For — We're especially interested in experts with deep, hands-on experience in: — Computational Chemistry & Electronic Structure — working with PySCF for quantum chemistry calculations including Hartree-Fock, DFT, TDDFT, CASSCF, and post-HF methods. Ideal candidates can design problems around excited-state analysis, orbital diagnostics, choosing the right method for tricky electronic structures, and interpreting computational artifacts that come from method limitations. — _Experience with other specialized software in this domain will also be considered._ — What Makes a Strong Candidate — You have graduate-level expertise (MS or PhD preferred) in the domain above, with real hands-on experience using these tools — not just theoretical knowledge. You've written code using these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated. — Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer. — Requirements • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience) • Proven proficiency with at least one of the listed scientific software libraries, shown through research publications, open-source contributions, or professional work • Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators • Ability to work independently and refine problem designs based on feedback • Comfortable working in a Linux/terminal environment with remote compute sandboxes • Available for at least 15–20 hours per week — Nice to Have • Experience across multiple listed domains or tools • Familiarity with benchmark or evaluation design • Background in scientific teaching or exam/problem-set design • Experience with computational reproducibility and containerized environments

$70 - $100 / hourOpen / Referral verified
STEM / Remote

Computational Particle & Nuclear Physics Expert

Particle & Nuclear Physics Expert — About the Project — We're building a large-scale benchmark to test how well advanced AI systems can solve hard scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data. — This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right. — What You'll Do — You'll create problems that require skilled use of specialized scientific software. Some will ask the AI to compute exact answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently. — Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty. — Domains & Tools We're Hiring For — We're especially interested in experts with deep, hands-on experience in: — Particle & Nuclear Physics — working with scikit-hep and related HEP Python tools for particle physics data analysis, cross-section computations, renormalization group calculations, and perturbative QCD. Experience with Monte Carlo event generation or collider phenomenology is a plus. — _Experience with other specialized software in this domain will also be considered._ — What Makes a Strong Candidate — You have graduate-level expertise (MS or PhD preferred) in the domain above, with real hands-on experience using these tools — not just theoretical knowledge. You've written code using these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated. — Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer. — Requirements • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience) • Proven proficiency with at least one of the listed scientific software libraries, shown through research publications, open-source contributions, or professional work • Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators • Ability to work independently and refine problem designs based on feedback • Comfortable working in a Linux/terminal environment with remote compute sandboxes • Available for at least 15–20 hours per week — Nice to Have • Experience across multiple listed domains or tools • Familiarity with benchmark or evaluation design • Background in scientific teaching or exam/problem-set design • Experience with computational reproducibility and containerized environments

$70 - $100 / hourOpen / Referral verified
STEM / Remote

Computational Astrophysics & Cosmology Expert

Computational Astrophysics & Cosmology Expert — About the Project — We're building a large-scale benchmark to test how well advanced AI systems can solve hard scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data. — This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right. — What You'll Do — You'll create problems that require skilled use of specialized scientific software. Some will ask the AI to compute exact answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently. — Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty. — Domains & Tools We're Hiring For — We're especially interested in experts with deep, hands-on experience in: — Astrophysics & Cosmology — working with astropy and related tools for cosmological calculations, angular power spectra, galaxy survey analysis, and observational data reduction pipelines. — _Experience with other specialized software in this domain will also be considered._ — What Makes a Strong Candidate — You have graduate-level expertise (MS or PhD preferred) in the domain above, with real hands-on experience using these tools — not just theoretical knowledge. You've written code using these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated. — Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer. — Requirements • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience) • Proven proficiency with at least one of the listed scientific software libraries, shown through research publications, open-source contributions, or professional work • Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators • Ability to work independently and refine problem designs based on feedback • Comfortable working in a Linux/terminal environment with remote compute sandboxes • Available for at least 15–20 hours per week — Nice to Have • Experience across multiple listed domains or tools • Familiarity with benchmark or evaluation design • Background in scientific teaching or exam/problem-set design • Experience with computational reproducibility and containerized environments

$70 - $100 / hourOpen / Referral verified
Code / Remote

Bioinformatics & Computational Single-Cell Genomics Expert

Bioinformatics & Computational Single-Cell Genomics Expert — About the Project — We're building a large-scale benchmark to test how well advanced AI systems can solve hard scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data. — This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right. — What You'll Do — You'll create problems that require skilled use of specialized scientific software. Some will ask the AI to compute exact answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently. — Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty. — Domains & Tools We're Hiring For — We're especially interested in experts with deep, hands-on experience in: — Bioinformatics & Single-Cell Genomics — working with tools like scanpy, scvelo, squidpy, and gudhi for single-cell RNA-seq analysis, trajectory inference, spatial transcriptomics, and topological data analysis. You should be comfortable designing problems around cell-type annotation, pseudotime ordering, multi-omic integration, spatial variable gene identification, and persistence-based analysis pipelines. This is our highest-throughput domain and where we're scaling first. — _Experience with other specialized software in this domain will also be considered._ — What Makes a Strong Candidate — You have graduate-level expertise (MS or PhD preferred) in the domain above, with real hands-on experience using these tools — not just theoretical knowledge. You've written code using these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated. — Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer. — Requirements • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience) • Proven proficiency with at least one of the listed scientific software libraries, shown through research publications, open-source contributions, or professional work • Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators • Ability to work independently and refine problem designs based on feedback • Comfortable working in a Linux/terminal environment with remote compute sandboxes • Available for at least 15–20 hours per week — Nice to Have • Experience across multiple listed domains or tools • Familiarity with benchmark or evaluation design • Background in scientific teaching or exam/problem-set design • Experience with computational reproducibility and containerized environments

$70 - $100 / hourOpen / Referral verified
Code / Remote

Computational Statistics and Applied Mathematics Expert (R, Python, and Matlab/Scilab)

Computational Statistics and Applied Mathematics Expert — About the Project — We're building a large-scale benchmark to test how well advanced AI systems can solve hard scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data. — This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right. — What You'll Do — You'll create problems that require skilled use of specialized statistical, mathematical, or scientific software packages. Some will ask the AI to compute reproducible numerical answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently. — Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty. — Domains & Tools We're Hiring For — We welcome statisticians and applied mathematicians working across a wide range of specializations. You do not need experience with every package listed below; strong expertise with one or more specialized computational packages is sufficient. — We're especially interested in experts with deep, hands-on experience using one or more specialized R or Python packages, including examples such as: • Bayesian statistics: rstan, cmdstanr, rjags, runjags, brms, rstanarm, nimble, bayesplot, posterior, loo • Item response theory and psychometrics: TAM, sirt, mirt, mirtCAT, eRm, ltm, lordif, psych • Structural equation and latent variable modelling: lavaan, semTools, OpenMx • Topological data analysis: TDAstats, TDApplied • Differential equations and dynamical systems: deSolve, pomp, FME • State-space and time-series modelling: KFAS, MARSS, forecast, vars, urca, rugarch, rmgarch, tseries, timeSeries • Survival and event-history analysis: survival, flexsurv, timereg, mets • Mixed, additive, and advanced regression models: lme4, nlme, mgcv, glmmTMB, TMB, quantreg, scam • Spatial statistics and geostatistics: spatstat, spatstat.geom, spatstat.linnet, spdep, gstat, geoR, spBayes, sf, stars, terra, lwgeom • Statistical learning and specialized modelling: mclust, kernlab, earth, pROC, multcomp, sandwich, effectsize, irr • Optimization and mathematical programming: lpSolve, linprog, nloptr, DEoptimR, SQUAREM • Numerical linear algebra and high-precision computation: RSpectra, Rmpfr, gmp, pracma • Computational geometry: geometry, deldir, polyclip — Other similar specialized statistical, mathematical, scientific, or domain-specific R packages will also be considered. Other similar specialized statistical or mathematical Python/Scilab packages are also welcome, such as statsmodels and PyMC. — Numerical computing and scientific modelling in Matlab/Scilab are also wanted. — What Makes a Strong Candidate — You have graduate-level expertise (MS or PhD required; PhD preferred, or MS with 10+ years of relevant experience) in statistics, applied mathematics, or a closely related quantitative field, with real hands-on experience using specialized computational packages — not just theoretical knowledge. — You have written code using one or more specialized statistical, mathematical, or scientific packages to solve actual research or professional problems, and you understand where these tools break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated. Deep expertise with one or more specialized computational packages is more important than familiarity with the entire package list above. — Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer. — Requirements • Graduate-level training in statistics, applied mathematics, a relevant STEM field, or equivalent research experience • Proven proficiency with at least one specialized statistical, mathematical, or scientific software package, demonstrated through research publications, open-source contributions, or professional work • Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators • Ability to work independently and refine problem designs based on feedback • Comfortable working in a Linux/terminal environment with remote compute sandboxes • Available for at least 15–20 hours per week — Nice to Have • Experience across multiple computational domains or specialized software packages • Familiarity with benchmark or evaluation design • Background in scientific teaching or exam/problem-set design • Experience with computational reproducibility and containerized environments

$70 - $90 / hourOpen / Referral verified
Code / United States Remote

LLM Red Team Specialist — Failure Modes & Edge Cases

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models. — 1. Overview — A leading AI lab is building the next generation of agentic evaluation benchmarks for frontier models and needs specialists who can find where those models break. Working in a red-teaming setup, you will design and probe complex, multi-step tasks to expose vulnerabilities, edge cases, and failure modes in frontier AI systems — the places where a model looks competent but is quietly wrong. — Each task represents one to two days of continuous, focused effort and spans multiple technical skills: coding, experimentation, and careful analysis. You will work in a tight feedback loop with the lab's researchers, turning the failure modes you find into stronger benchmark tasks. — This is a full-time W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI lab as part of their extended workforce. This role is fully remote within the United States, at approximately 35 hours per week. — 2. Key Responsibilities • Probe models: Explore how frontier AI models behave on coding, ML, and analysis tasks, and find the spots where they quietly get things wrong. • Design challenges: Turn the weaknesses you find into well-crafted tasks that are hard for models but fair to grade. • Document findings: Write up what you discover clearly, with evidence and steps others can reproduce. • Strengthen tasks: Team up with task authors to close loopholes, shortcuts, and grading gaps. • Work as a team: Share insights with researchers and fellow experts so the benchmark keeps getting better. — 3. Core Qualifications • MSc or PhD in a STEM field, or equivalent practical experience in a research-heavy domain requiring data analysis and coding. • 1+ years of experience in a research, research-engineering, security, or AI-evaluation role. • Demonstrated ability to identify vulnerabilities, edge cases, or failure modes in LLMs or ML systems — through red teaming, adversarial testing, security research, or rigorous model evaluation. • Working proficiency in Python and Git, with the ability to script your own probes and analyses. • Strong familiarity with LLM capabilities, limitations, and evaluation techniques. • Past experience in AI training, model evaluation, or benchmark/task authoring is preferred. • A perfectionist mindset: high attention to detail, creativity in finding what others missed, strong written communication, and the ability to work independently through ambiguous, open-ended problems. • Ability to engage reliably for approximately 35 hours per week. — About Cincinnatus LLC — Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. — Roles hired through Cincinnatus are not project-based or freelance engagements. They are structured, role-based positions that typically involve part-time or full-time commitments, close collaboration with a client's internal teams, and integration into standard enterprise workflows. — Cincinnatus is a legal entity separate from Mercor. While opportunities may be discovered through Mercor's platform, employment, onboarding, payroll, and benefits for these roles are administered by Cincinnatus LLC. — Equal Employment Opportunity — Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic. — Cincinnatus is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans throughout the job application process.

$60 - $90 / hourOpen / Referral verified
Code / United States Remote

QA/Test Engineer

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models. — 1. Overview — A leading AI lab is building the next generation of agentic evaluation benchmarks for frontier models, and complex multi-step tasks are only useful if they are airtight: unambiguous, correctly graded, and robust to shortcuts. We are seeking experienced QA and test engineers to be the quality backbone of this benchmark — designing the test cases and review processes that guarantee every task measures what it claims to measure. — Each task under review represents one to two days of expert effort and spans multiple technical skills, so quality review here means genuinely understanding the task: running it, probing its edge cases, and debugging its environment. You will work in a tight feedback loop with the lab's researchers and task authors. — This is a full-time W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI lab as part of their extended workforce. This role is fully remote within the United States, at approximately 35 hours per week. — 2. Key Responsibilities • Design checks: Create test cases that confirm each task works as intended — including the tricky edge cases. • Review tasks: Give tasks and reference solutions a careful read before they're finalized, catching ambiguity and gaps early. • Debug: Roll up your sleeves in Python when a task or its checks don't behave the way they should. • Shape the process: Help build simple, repeatable quality checklists, and share feedback authors can act on right away. • Protect the results: Watch for shortcuts and grading gaps in AI agent runs so benchmark scores stay trustworthy. — 3. Core Qualifications • MSc or PhD in a STEM field, or equivalent practical experience in a research-heavy or engineering-heavy domain. • 1+ years of experience in test engineering, quality assurance, or a research/software engineering role with strong quality ownership. • Demonstrated skill designing test cases and quality-review processes, and debugging complex systems end-to-end. • Working proficiency in Python and Git, and comfort navigating unfamiliar codebases and environments. • Exceptional attention to detail and clear written documentation habits. • Past experience in AI training, model evaluation, or quality review of AI-generated work is preferred. • A perfectionist mindset: creativity in finding what others missed, and the ability to work independently through ambiguous, open-ended problems. • Ability to engage reliably for approximately 35 hours per week. — About Cincinnatus LLC — Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. — Roles hired through Cincinnatus are not project-based or freelance engagements. They are structured, role-based positions that typically involve part-time or full-time commitments, close collaboration with a client's internal teams, and integration into standard enterprise workflows. — Cincinnatus is a legal entity separate from Mercor. While opportunities may be discovered through Mercor's platform, employment, onboarding, payroll, and benefits for these roles are administered by Cincinnatus LLC. — Equal Employment Opportunity — Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic. — Cincinnatus is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans throughout the job application process.

$60 - $90 / hourOpen / Referral verified
Medical / United States Remote

STEM Researcher — Computational Fields

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models. — 1. Overview — A leading AI lab is building the next generation of agentic evaluation benchmarks for frontier models and is recruiting researchers from computational STEM fields — as well as computationally heavy social sciences and humanities — to bring working-researcher rigor to benchmark design. You will translate the scientific method — experimental design, hypothesis testing, and rigorous evaluation — into complex, multi-step tasks that today's best models cannot yet complete reliably. — Each task represents one to two days of continuous, focused effort and spans multiple skills: study design, implementation in code, data analysis, and careful written conclusions. You will work in a tight feedback loop with the lab's researchers, surfacing the kinds of methodological mistakes a working researcher would catch immediately. — This is a full-time W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI lab as part of their extended workforce. This role is fully remote within the United States, at approximately 35 hours per week. — 2. Key Responsibilities • Design tasks: Turn the research skills you use every day — designing studies, testing hypotheses, evaluating results — into engaging, multi-step tasks. • Author solutions: Work through your own tasks in Python and notebooks, at the level of rigor you'd expect from a careful colleague. • Define what good looks like: Help spell out what separates sound scientific reasoning from reasoning that merely sounds right. • Evaluate models: Review model attempts at your tasks and flag the mistakes a working researcher would spot right away. • Work as a team: Compare notes with researchers and fellow experts to keep evaluations consistent and accurate. — 3. Core Qualifications • MSc or PhD in a STEM field, or in a computational social-science or humanities discipline, or equivalent practical experience in a research-heavy domain requiring data analysis and coding. • 1+ years of experience in an active research role (academia, industry, or national labs). • Your own research involves significant computational work: Python-based analysis, simulation, modeling, or data pipelines. • Strong grounding in experimental design, hypothesis testing, and rigorous evaluation of results. • Working familiarity with Git, IDEs, and notebook environments (Jupyter or Colab). • Past experience in AI training, model evaluation, or benchmark/task authoring is preferred. • A perfectionist mindset: high attention to detail, creativity in task design, strong written communication, and the ability to work independently through ambiguous, open-ended problems. • Ability to engage reliably for approximately 35 hours per week. — About Cincinnatus LLC — Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. — Roles hired through Cincinnatus are not project-based or freelance engagements. They are structured, role-based positions that typically involve part-time or full-time commitments, close collaboration with a client's internal teams, and integration into standard enterprise workflows. — Cincinnatus is a legal entity separate from Mercor. While opportunities may be discovered through Mercor's platform, employment, onboarding, payroll, and benefits for these roles are administered by Cincinnatus LLC. — Equal Employment Opportunity — Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic. — Cincinnatus is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans throughout the job application process.

$60 - $90 / hourOpen / Referral verified
Math / United States Remote

Data Science & Quantitative Analysis Expert

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models. — 1. Overview — A leading AI lab is building the next generation of agentic evaluation benchmarks for frontier models and needs experienced data scientists and quantitative analysts to act as ground-truth experts. You will design complex analysis tasks that simulate real research work — for example, comparing two anomaly-detection algorithms on a dataset, calculating correlations, performing manual spot checks, and summarizing the findings in a notebook clear enough to drive a researcher's decision. — Each task represents one to two days of continuous, focused effort and spans multiple skills: data cleaning, statistical analysis, interpretation, and clear reporting. You will work in a tight feedback loop with the lab's researchers, verifying exactly where and why frontier models fall short on rigorous analytical work. — This is a full-time W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI lab as part of their extended workforce. This role is fully remote within the United States, at approximately 35 hours per week. — 2. Key Responsibilities • Design tasks: Create realistic data-analysis challenges — cleaning messy data, comparing methods, interpreting results — based on the kind of analysis you do every day. • Author notebooks: Work through your own tasks in Jupyter or Colab, producing clear, reproducible reference analyses. • Compare methods: Build tasks that ask for a fair comparison between analytical approaches, backed by spot checks and a clear recommendation. • Evaluate models: Review how models handle your tasks, and check whether their statistics and conclusions actually hold up. • Work as a team: Compare notes with researchers and fellow experts to keep evaluations consistent and accurate. — 3. Core Qualifications • MSc or PhD in statistics, data science, or another quantitative STEM field, or equivalent practical experience in a research-heavy analytical domain. • 1+ years of experience in a research, research-engineering, or heavy data-analysis role. • Deep hands-on data-analysis skills: data cleaning, statistical correlation, hypothesis testing, and careful interpretation of results. • Proficiency with Jupyter Notebooks or Google Colab for analysis and reporting. • Working proficiency in Python (pandas, NumPy, or similar) and Git. • Strong ability to communicate analytical findings in writing for decision-makers. • Past experience in AI training, model evaluation, or benchmark/task authoring is preferred. • A perfectionist mindset: high attention to detail, creativity in task design, and the ability to work independently through ambiguous, open-ended problems. • Ability to engage reliably for approximately 35 hours per week. — About Cincinnatus LLC — Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. — Roles hired through Cincinnatus are not project-based or freelance engagements. They are structured, role-based positions that typically involve part-time or full-time commitments, close collaboration with a client's internal teams, and integration into standard enterprise workflows. — Cincinnatus is a legal entity separate from Mercor. While opportunities may be discovered through Mercor's platform, employment, onboarding, payroll, and benefits for these roles are administered by Cincinnatus LLC. — Equal Employment Opportunity — Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic. — Cincinnatus is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans throughout the job application process.

$60 - $90 / hourOpen / Referral verified
Code / United States Remote

Machine Learning Engineer — Model Evaluation & Experimentation

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models. — 1. Overview — A leading AI lab is building the next generation of agentic evaluation benchmarks for frontier models and needs experienced machine learning practitioners to act as ground-truth experts for model evaluation and experimentation. You will author complex, multi-step ML tasks — for example, taking a vague research idea like "modify how an RL reward is computed," implementing the change, running the training experiment, and analyzing the results to determine success — and verify exactly where frontier models fall short. — Each task represents one to two days of continuous, focused effort and spans multiple technical skills: implementation, experiment setup and execution, and rigorous analysis. You will work in a tight feedback loop with the lab's researchers. — This is a full-time W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI lab as part of their extended workforce. This role is fully remote within the United States, at approximately 35 hours per week. — 2. Key Responsibilities • Design tasks: Turn real ML research ideas — like tweaking how an RL reward is computed — into well-defined, multi-step tasks. • Run experiments: Implement changes, run training experiments, and analyze the results to show what a correct solution looks like. • Explore RL ideas: Build some of your tasks around reinforcement-learning basics such as reward functions and training behavior. • Evaluate models: See how frontier models handle your tasks, and note where and why they fall short. • Work as a team: Compare notes with researchers and fellow experts so tasks stay consistent, rigorous, and fair. — 3. Core Qualifications • MSc or PhD in machine learning, computer science, or another STEM field, or equivalent practical experience in a research-heavy domain. • 1+ years of experience in a research or research-engineering role. • Hands-on experience training and evaluating ML models and running experiments end-to-end — experiment setup, execution, and analysis — not just using ML libraries superficially. • Strong familiarity with large language models: their capabilities, limitations, and evaluation techniques. • Working proficiency in Python and Git, with comfort in both scripting and notebook environments. • Basic understanding of reinforcement learning (reward functions, policy training) is preferred. • Past experience in AI training, model evaluation, or benchmark/task authoring is preferred. • A perfectionist mindset: high attention to detail, creativity in task design, strong written communication, and the ability to work independently through ambiguous, open-ended problems. • Ability to engage reliably for approximately 35 hours per week. — About Cincinnatus LLC — Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. — Roles hired through Cincinnatus are not project-based or freelance engagements. They are structured, role-based positions that typically involve part-time or full-time commitments, close collaboration with a client's internal teams, and integration into standard enterprise workflows. — Cincinnatus is a legal entity separate from Mercor. While opportunities may be discovered through Mercor's platform, employment, onboarding, payroll, and benefits for these roles are administered by Cincinnatus LLC. — Equal Employment Opportunity — Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic. — Cincinnatus is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans throughout the job application process.

$60 - $90 / hourOpen / Referral verified
Code / United States Remote

Software Engineering Expert

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models. — 1. Overview — A leading AI lab is building the next generation of agentic evaluation benchmarks for frontier models and needs experienced software engineers to act as task curators. You will design, implement, and review complex, multi-step engineering tasks that simulate the real-world challenges research engineers face — realistic, genuinely hard problems that today's best AI coding agents cannot yet solve reliably. — Each task represents one to two days of continuous, focused effort and spans multiple technical skills: Python implementation, environment and tooling setup, debugging, and clear documentation. You will work in a tight feedback loop with the lab's researchers, verifying exactly where and why frontier models fail on your tasks. — This is a full-time W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI lab as part of their extended workforce. This role is fully remote within the United States, at approximately 35 hours per week. — 2. Key Responsibilities • Design tasks: Create realistic, multi-step software engineering challenges — the kind of work you'd actually do on the job — that push the limits of today's best AI coding agents. • Build reference solutions: Solve your own tasks in Python, with the setup and checks needed so each task has a clear, verifiable answer. • Work with AI tools: Use AI coding assistants as part of your everyday workflow, and observe where they help and where they fall short. • Review and refine: Look over tasks built by fellow experts and share feedback on clarity, correctness, and difficulty. • Learn from failures: See how AI agents attempted your tasks and help the research team understand what tripped them up. — 3. Core Qualifications • MSc or PhD in computer science or another STEM field, or equivalent practical experience in a research-heavy domain requiring significant coding and data analysis. • 1+ years of experience in a research, research-engineering, or software engineering role. • Strong hands-on Python scripting and debugging skills, with clean-code habits and attention to readability. • Everyday fluency with version control (Git), IDEs, and standard software development workflows. • Experience with AI coding assistants, prompt engineering, or agent workflows is preferred. • Past experience in AI training, model evaluation, or benchmark/task authoring is preferred. • A perfectionist mindset: high attention to detail, creativity in task design, strong written communication, and the ability to work independently through ambiguous, open-ended problems. • Ability to engage reliably for approximately 35 hours per week. — About Cincinnatus LLC — Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. — Roles hired through Cincinnatus are not project-based or freelance engagements. They are structured, role-based positions that typically involve part-time or full-time commitments, close collaboration with a client's internal teams, and integration into standard enterprise workflows. — Cincinnatus is a legal entity separate from Mercor. While opportunities may be discovered through Mercor's platform, employment, onboarding, payroll, and benefits for these roles are administered by Cincinnatus LLC. — Equal Employment Opportunity — Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic. — Cincinnatus is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans throughout the job application process.

$60 - $90 / hourOpen / Referral verified
Code / Remote

Computational Electrical Engineering & RF/Circuit Design Expert

Electrical Engineering & RF/Circuit Design Expert — About the Project — We're building a large-scale benchmark to test how well advanced AI systems can solve hard scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data. — This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right. — What You'll Do — You'll create problems that require skilled use of specialized scientific software. Some will ask the AI to compute exact answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently. — Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty. — Domains & Tools We're Hiring For — We're especially interested in experts with deep, hands-on experience in: — Electrical Engineering & RF/Circuit Design — working with scikit-rf for RF and microwave network analysis, S-parameter characterization, and transmission-line modeling, or ngspice for circuit simulation, operating point analysis, and frequency response characterization. Candidates should be comfortable designing problems that involve recovering circuit parameters from measurement data. — _Experience with other specialized software in this domain will also be considered._ — What Makes a Strong Candidate — You have graduate-level expertise (MS or PhD preferred) in the domain above, with real hands-on experience using these tools — not just theoretical knowledge. You've written code using these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated. — Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer. — Requirements • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience) • Proven proficiency with at least one of the listed scientific software libraries, shown through research publications, open-source contributions, or professional work • Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators • Ability to work independently and refine problem designs based on feedback • Comfortable working in a Linux/terminal environment with remote compute sandboxes • Available for at least 15–20 hours per week — Nice to Have • Experience across multiple listed domains or tools • Familiarity with benchmark or evaluation design • Background in scientific teaching or exam/problem-set design • Experience with computational reproducibility and containerized environments

$70 - $85 / hourOpen / Referral verified
Code / Remote

Computational Structural & Mechanical Engineering Expert

Computational Structural & Mechanical Engineering Expert — About the Project — We're building a large-scale benchmark to test how well advanced AI systems can solve hard computational scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data. — This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right. — What You'll Do — You'll create problems that require skilled use of specialized scientific software. Some will ask the AI to compute exact answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently. — Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty. — Domains & Tools We're Hiring For — We're especially interested in experts with deep, hands-on experience with open-source, domain-specific computational tools such as FEniCSx/DOLFINx, scikit-fem, OpenFOAM, deal.II, MFEM, MOOSE, CalculiX, Elmer FEM, Code\_Aster, SfePy, FiPy, Devito, Cantera, CoolProp, Pyomo, or SimPy, for finite-element analysis, computational mechanics, structural analysis, elasticity, CFD, multiphysics simulation, heat and mass transfer, thermodynamics, combustion, fluid mechanics, HVAC/thermal systems, manufacturing simulation, optimization, or thermophysical-property calculations. — Relevant work may include beam, plate, and shell analysis; linear or nonlinear elasticity; finite-element and variational formulations; mesh refinement and convergence studies; continuum and solid mechanics; computational fluid dynamics; coupled multiphysics problems; thermal-fluid simulation; structural or system optimization; reliability analysis; and related numerical engineering workflows. — Experience with underlying theories and numerical methods — such as Euler–Bernoulli and Timoshenko beam theory, continuum mechanics, finite-element methods, Galerkin/variational methods, finite-volume methods, PDE discretization, constitutive modeling, thermodynamics, numerical linear algebra, and nonlinear solution methods — is valuable. — Experience with other open-source computational structural or mechanical engineering software will also be considered, including scientific codes and solver frameworks built with Python, C, C++, or Fortran. — What Makes a Strong Candidate — You have graduate-level expertise (MS or PhD preferred) in the domain above, with real hands-on experience using these tools — not just theoretical knowledge. You've written code using these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated. — Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer. — Requirements • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience) • Proven proficiency with at least one of the listed scientific software libraries, shown through research publications, open-source contributions, or professional work • Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators • Ability to work independently and refine problem designs based on feedback • Comfortable working in a Linux/terminal environment with remote compute sandboxes • Available for at least 15–20 hours per week — Nice to Have • Experience across multiple listed domains or tools • Familiarity with benchmark or evaluation design • Background in scientific teaching or exam/problem-set design • Experience with computational reproducibility and containerized environments

$70 - $85 / hourOpen / Referral verified
STEM / Remote

Computational Seismology & Geophysics Expert

Computational Seismology & Geophysics Expert — About the Project — We're building a large-scale benchmark to test how well advanced AI systems can solve hard scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data. — This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right. — What You'll Do — You'll create problems that require skilled use of specialized scientific software. Some will ask the AI to compute exact answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently. — Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty. — Domains & Tools We're Hiring For — We're especially interested in experts with deep, hands-on experience in: — Computational Seismology & Geophysics — hands-on experience with open-source, domain-specific computational tools such as SPECFEM, ObsPy, Pyrocko, SimPEG, pyGIMLi, SeisBench, EQcorrscan, or Fatiando a Terra, for seismic wave propagation and numerical simulation, synthetic seismogram generation, full-waveform inversion (FWI), seismic imaging, travel-time tomography, moment tensor inversion, event detection/location, or related computational geophysics workflows. — Experience with other open-source computational seismology or geophysics software will also be considered, including tools and scientific codes built with Python, C, C++, or Fortran. — What Makes a Strong Candidate — You have graduate-level expertise (MS or PhD preferred) in the domain above, with real hands-on experience using these tools — not just theoretical knowledge. You've written code using these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated. — Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer. — Requirements • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience) • Proven proficiency with at least one of the listed scientific software libraries, shown through research publications, open-source contributions, or professional work • Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators • Ability to work independently and refine problem designs based on feedback • Comfortable working in a Linux/terminal environment with remote compute sandboxes • Available for at least 15–20 hours per week — Nice to Have • Experience across multiple listed domains or tools • Familiarity with benchmark or evaluation design • Background in scientific teaching or exam/problem-set design • Experience with computational reproducibility and containerized environments

$70 - $85 / hourOpen / Referral verified
STEM / Remote

Computational Pharmacokinetics & Systems Biology Expert

Computational Pharmacokinetics & Systems Biology Expert — About the Project — We're building a large-scale benchmark to test how well advanced AI systems can solve hard scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data. — This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right. — What You'll Do — You'll create problems that require skilled use of specialized scientific software. Some will ask the AI to compute exact answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently. — Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty. — Domains & Tools We're Hiring For — We're especially interested in experts with deep, hands-on experience in: — Pharmacokinetics & Systems Biology — working with libRoadRunner, Tellurium, or SBML-based tools for compartmental PK/PD modeling, enzyme kinetics, or systems biology simulations. — _Experience with other specialized software in this domain will also be considered._ — What Makes a Strong Candidate — You have graduate-level expertise (MS or PhD preferred) in the domain above, with real hands-on experience using these tools — not just theoretical knowledge. You've written code using these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated. — Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer. — Requirements • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience) • Proven proficiency with at least one of the listed scientific software libraries, shown through research publications, open-source contributions, or professional work • Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators • Ability to work independently and refine problem designs based on feedback • Comfortable working in a Linux/terminal environment with remote compute sandboxes • Available for at least 15–20 hours per week — Nice to Have • Experience across multiple listed domains or tools • Familiarity with benchmark or evaluation design • Background in scientific teaching or exam/problem-set design • Experience with computational reproducibility and containerized environments

$70 - $85 / hourOpen / Referral verified
Code / United States Remote

Software Engineer, Full Stack (Python, Java, Rust, C#, C++)

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models. — 1. Overview — Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're seeking talented Full-Stack Software Engineers with hands-on production experience across modern application stacks — Python, Java, Rust, C#, C++, and TypeScript — to build, integrate, and stress-test real software on top of frontier models before they ship. Engineers work directly with the AI lab's engineering manager on fast-moving projects and are expected to onboard quickly and contribute working code early. This is a full-time commitment of 40 hours per week. — This is a W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI Lab as part of their extended workforce. — 2. Key Responsibilities • Build and ship full-stack applications, services, and internal tools — in Python, Java, Rust, C#, C++, or TypeScript — that exercise frontier model capabilities end to end. • Integrate pre-release model APIs into working software, including the surrounding scaffolding: tool interfaces, evaluation harnesses, and telemetry. • Diagnose and document model and integration failure modes surfaced while building, translating engineering observations into clear written feedback for the research team. • Prototype quickly against shifting requirements, delivering working increments with limited up-front specification. • Collaborate with the engineering manager and other engineers to maintain consistency in code quality, architecture, and technical documentation. — 3. Core Qualifications • 3+ years of dedicated professional experience building and shipping production software at a recognized, top-tier organization. • Production experience in at least one of Python, Java, Rust, C#, or C++, plus working proficiency in a second language — this cohort is intentionally staffed across multiple language ecosystems. • Hands-on experience across the stack: backend services and APIs, a modern front-end framework (React or equivalent), relational or document databases, and cloud deployment. • Demonstrated ability to onboard onto an unfamiliar codebase and deliver working code quickly with minimal ramp-up. • Demonstrable career progression. • Ability to engage reliably for at least 40 hours/week during weekdays. • Strong written communication skills and the ability to explain complex technical decisions clearly. — About Cincinnatus LLC: Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. — Equal Employment Opportunity: Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic.

$50 - $65 / hourOpen / Referral verified
Math / Remote

Data Science and Analytics Experts

Role Overview • Mercor is seeking senior data science and analytics professionals to build evaluation tasks for AI systems operating in Fortune 500 enterprise data and analytics contexts. • The workflows are calibrated to the data scale, model complexity, and business-critical stakes of Fortune 500 and large public company data operations. • Contributors design enterprise data science scenarios, draft reference outputs, and write rubrics that capture how senior F500 data leaders think. — Key Responsibilities • Construct enterprise data science scenarios spanning large-scale predictive modeling, multi-stakeholder analytics governance, and complex data infrastructure decisions at F500 accounts. • Build analytics tasks across F500 machine learning model development, enterprise data pipelines, business intelligence at scale, experimentation/causal inference, and data strategy. • Develop data and MLOps scenarios involving tools such as Snowflake, Databricks, Python/R, SQL, Tableau/Power BI, and enterprise ML platforms (SageMaker, Vertex AI, MLflow) in F500 stacks. • Apply enterprise data science methodologies (statistical rigor, A/B testing frameworks, model validation, MLOps best practices) and produce reference analyses, model documentation, and executive-level insights. • Author rubrics that distinguish authentic enterprise data science judgment from generic textbook or tutorial-level recall. — Ideal Qualifications • 5+ years working as a data scientist, analytics leader, or ML engineer at a Fortune 500 technology or enterprise organization (Google, Meta, Amazon, Microsoft, Netflix) or inside an F500 data/analytics organization (JPMorgan, UPS, Unilever, PepsiCo, Walmart). • Direct ownership of F500 data products, F500 analytics initiatives, or F500 machine learning systems in production. • Fluency in enterprise data science tooling and methodologies, plus understanding of how F500 data governance, privacy compliance, and cross-functional stakeholder alignment actually work. • Prior rubric, technical curriculum, or model documentation authorship is a plus.

$60 - $70 / hourOpen / Referral verified
Code / India Remote

Software Engineer, Full Stack — India

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models. — 1. Overview — Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're seeking talented Full-Stack Software Engineers with hands-on production experience across modern application stacks — Python, Java, Rust, C#, C++, and TypeScript — to build, integrate, and stress-test real software on top of frontier models before they ship. Engineers work directly with the AI lab's engineering manager on fast-moving projects and are expected to onboard quickly and contribute working code early. — This is a full-time engagement of 40 hours per week. — 2. Key Responsibilities • Build and ship full-stack applications, services, and internal tools — in Python, Java, Rust, C#, C++, or TypeScript — that exercise frontier model capabilities end to end. • Integrate pre-release model APIs into working software, including the surrounding scaffolding: tool interfaces, evaluation harnesses, and telemetry. • Diagnose and document model and integration failure modes surfaced while building, translating engineering observations into clear written feedback for the research team. • Prototype quickly against shifting requirements, delivering working increments with limited up-front specification. • Collaborate with the engineering manager and other engineers to maintain consistency in code quality, architecture, and technical documentation. — 3. Core Qualifications • 3+ years of dedicated professional experience building and shipping production software at a recognized, top-tier organization. • Production experience in at least one of Python, Java, Rust, C#, or C++, plus working proficiency in a second language — this cohort is intentionally staffed across multiple language ecosystems. • Hands-on experience across the stack: backend services and APIs, a modern front-end framework (React or equivalent), relational or document databases, and cloud deployment. • Demonstrated ability to onboard onto an unfamiliar codebase and deliver working code quickly with minimal ramp-up. • Demonstrable career progression. • Ability to engage reliably for at least 40 hours/week during weekdays. • Strong written communication skills and the ability to explain complex technical decisions clearly.

$25 - $30 / hourOpen / Referral verified
Finance / Hyderabad Onsite

Fraud Analyst – Content & Reviews Abuse

About the Role — You'll join a trust & safety function protecting a high-traffic, consumer-facing platform from fraud and abuse. Partnering with product, engineering, and operations stakeholders, you'll investigate ambiguous, evolving abuse patterns — applying investigative rigor and creative analysis to get to root cause. Over time, you'll build specialized subject-matter expertise across the many forms this abuse can take. — We're looking for candidates with a track record in fraud detection, investigation, and risk assessment — reviewing transactions, spotting anomalies in data, and evaluating exposure. This background could come from insurance fraud, forensic accounting, banking/financial crimes, or similar. Certifications such as CFE or ACFE are a nice-to-have, not required. — What You'll Do • Investigate ambiguous cases end-to-end, turning findings into data-backed conclusions that keep user trust as the top priority • Pull together varied data sources and signals to trace deceptive or manipulative activity, and help design new detection experiments • Document findings clearly — a well-reasoned narrative backed by concrete evidence — so others can act on your conclusions — Work Setup • Full-time, onsite in India • Must be available to work India Standard Time hours • Requires a private, secure workspace (no shared or public settings), given the sensitivity of the content involved • Prior experience working on a Mercor project is mandatory — Minimum Qualifications • Bachelor's degree in a technical discipline, or equivalent hands-on experience • 4+ years analyzing data — spotting trends, building summary stats, turning raw data into decisions • 4+ years working end-to-end on ambiguous, open-ended analytical projects • Comfortable with SQL and Python for analysis; strong problem-solving instincts and efficient execution • Strong written/verbal communication, including translating dense policy concepts into plain language • Track record presenting analytical findings to senior stakeholders • Able to produce thorough case write-ups and detailed observation notes — Preferred Qualifications • Familiarity with how fraud/abuse evolves on online platforms over time • Background in program or policy management, customer/merchant experience, or business strategy • Exposure to content moderation, policy enforcement, customer support, or policy design • Sharp problem-solving and critical-thinking instincts with strong attention to detail • Some familiarity with AI/ML or generative AI concepts • CFE/ACFE certification a plus

$15 - $25 / hourOpen / Referral verified