Dataset Enablement Manager(Applied Engineering)

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.