Posted over 30 days ago. Roles like this often stay open for a while, so it's still worth applying.
Dataset Enablement Manager at Turing
posted 1 month agoDataset Enablement Manager (Frontier Sciences & Math) | Contractor | Worldwide Remote
Turing is looking for a Dataset Enablement Manager to bridge the gap between complex scientific data pipelines and commercial teams. You'll package technical datasets into compelling collateral, train client-facing teams on domain-specific benchmarks, and drive multi-client sell-through of Turing's off-the-shelf dataset portfolio to leading global AI labs.
Engagement: 8-week contract | Min. 4 hrs/day, up to 40 hrs/week | 4-hour PST overlap required
About Turing
Turing is one of the world's fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems. Turing partners with leading AI labs to advance frontier model capabilities in reasoning, coding, STEM, and multimodality — and leverages that expertise to build real-world AI solutions for enterprise clients.
Key Responsibilities
- Pipeline Tracking: Maintain real-time visibility into active dataset pipelines across all frontier science and math teams.
- Collateral & Sample Packaging: Develop sample packs, schema definitions, and benchmark comparisons to clearly communicate dataset value to stakeholders.
- Commercial Enablement & Training: Lead regular deep-dives for client-facing teams, introducing new dataset offerings and articulating customer value propositions.
- Sell-Through Performance: Drive multi-client monetization, identify under-utilized datasets, and track and report on sell-through performance metrics.
Requirements
- 3–6 years of experience in technical enablement, pre-sales engineering, technical product marketing, or applied research consulting.
- Strong conceptual understanding of scientific benchmarks, algorithmic problem-solving, and LLM reasoning/evaluation mechanics.
- Exceptional English communication skills (verbal and written) with a proven track record collaborating with US-based engineering and research teams.
Education
- Bachelor's or Master's degree in Mathematics, Physics, Chemistry, Computational Biology, Computer Science, or a related field.
- Experience in AI evaluation, data annotation, content review, or quality assurance is a plus.
Evaluation Process
- Shortlisted candidates will receive a Job Interest Form.
- Final candidates will be contacted with next steps and onboarding details.