Dataset Enablement Manager(Applied Engineering)

Official role description

We are seeking a Dataset Enablement Manager to bridge the technical gap between scientific data pipelines and centralized commercial teams. In this role, you will package complex technical datasets into high-impact collateral, educate client-facing teams on domain-specific benchmarks, and drive the multi-client sell-through of our OTS dataset portfolio to leading global AI labs.

Official job description checked 2026-10-24:

About Turing

Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems.

Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM, and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.

Role Overview

We are seeking a Dataset Enablement Manager to bridge the technical gap between scientific data pipelines and centralized commercial teams. In this role, you will package complex technical datasets into high-impact collateral, educate client-facing teams on domain-specific benchmarks, and drive the multi-client sell-through of our OTS dataset portfolio to leading global AI labs.

Requirements

Experience: 6+ years of professional experience in technical enablement, pre-sales engineering, technical product marketing, or applied research consulting.

Domain Fluency: Strong conceptual foundation in scientific benchmarks, algorithmic problem-solving, and LLM evaluation and reasoning mechanics.

Communication: Exceptional written and verbal English communication, with a proven track record collaborating directly with US-based research scientists, engineering leads, and commercial executives.

Analytical & Collateral Skills: Hands-on experience structuring technical documentation, schema specs, and performance dashboards for technical audiences.

Responsibilities

Pipeline Tracking & Visibility: Maintain real-time oversight of active dataset pipelines across all frontier science, math, and scientific software engineering teams.

Technical Collateral & Sample Packaging: Assemble production-grade sample packs, schema definitions, benchmark comparisons, and technical documentation to effectively showcase dataset quality.

Commercial Enablement & Training: Lead regular deep-dives and training sessions for sales, account, and solutions teams to communicate value propositions, methodology, and target LLM use cases.

Sell-Through Performance & Monetization: Track multi-client utilization metrics, identify under-monetized dataset assets, and drive performance reporting to maximize commercial sell-through.

Cross-Functional Bridge: Serve as the primary technical interface between dataset development teams and centralized commercial/go-to-market leaders.

Education & Experience

Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, Materials Science, or a related discipline.

Experience in AI evaluation, data annotation, content review, quality assurance, or a related analytical role is preferred but not required.

Offer Details:

Commitments Required: at least 4 hours per day and upto 40 hours per week with 4 hours of overlap with PST.

Engagement type: Contractor

Engagement Length:  8 weeks

Evaluation Process -

Shortlisted candidates will be sent a Job Interest Form.

Final selected candidates will be contacted with the next steps and onboarding requirements.

Confirm current eligibility, workload and final terms with Turing. Referral rewards are separate from applicant compensation.