What the work is
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.
Who gets hired
- 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.
Pay
See listing, fully remote. How payouts and tax work.
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