Frontier Data Strategist

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About the role

Frontier AI labs decide what direction their models need to take before the actual training starts. As a Frontier Data Strategist on Scale's Generative AI team, you'll play a significant part in those conversations. You'll work directly with researchers at the world's leading AI labs to work out what data the next evolution of their models will need, then design the human-data programs to deliver it. You'll sit where frontier research meets Scale's product roadmap. With customers, you'll build deep, technical relationships with researchers, learn where their work is heading, and bring them new data ideas before they ask or sometimes even think of it themselves. Inside Scale, you'll work with our AI Product Managers, ML Research, Delivery Operations, and Engagement Management teams to design what we're building to meet customer needs, turning research directions into product priorities. This is a forward-looking, highly cross-functional role. Our Engagement Managers own customer success for live programs; Frontier Data Strategists own all that comes before it: spotting the need, designing the program, scoping and forecasting it, and winning the work. Through this role you’ll work closely with leading minds in the industry to push the frontier of AI science. What you’ll do: • Build trusted relationships with researchers at your assigned frontier labs, and become a technical thought partner on their post-training, evaluation, and agent work. • Anticipate customer data needs by understanding their research priorities, following the literature, and tracking where model capabilities are heading. • Work cross-functionally to design new human-data programs (task design, data specs, quality bars, expert profiles) that turn loosely defined research goals into concrete projects Scale can run. • Match customer needs to Scale's product roadmap, working with AI product managers and ML teams to decide what to build, prioritize, or adapt. • Bring insights from the frontier (research directions, emerging data needs, capability gaps) back to Scale's technical teams to guide roadmap and investment decisions. • Scope, forecast, and price new opportunities with Delivery, Growth Operations, and Finance, and see them through to signed work and a clean handoff to Delivery Operations and Engagement Management. What we’re looking for: • 3+ years in a technical AI/ML role, such as ML engineering, research, applied science, technical product management, or post-training data work at a lab or data provider. • Working fluency in the LLM training lifecycle, especially post-training: SFT, preference data, reward modeling, RL environments, evaluations, etc. • The ability to read a research paper and form a view on what data would improve a given capability. • Experience earning credibility with technical stakeholders through substance, and enjoying the relationship side of the work. • Comfort turning ambiguous requests into structured plans with clear scope, timelines, and resource estimates. • A degree in CS, engineering, math, physics, or another quantitative field. Ideally you'd have: • Hands-on experience designing training data, evals, or RL environments. • Experience at a frontier lab, model developer, or AI data company. • Some customer-facing experience in pre-sales, solutions engineering, or technical consulting. • Experience founding a company or early-stage startup leadership experience. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and add

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