Frontier Data Strategist

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 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 BenefitsHealth & Wellbeing: Our holistic approach to supporting Scaliens includes comprehensive health coverage, dental and vision insurance, mental healthcare services, and more. PTO policies and accommodating schedules ensure you’ll get time off when you need it to relax and recharge. Note that our offerings may vary by region as we strive to respond to the unique needs of Scaliens around the globe. Personal & Career Growth: Continuously learn and grow through annual learning & development stipend, attending leadership breakfasts, manager training, speaker series, and joining an ERG. Building Scale Community: We welcome guests to our offices, and you can expect to see Scalien families and friends around. Join local happy hours, and accept invites to game nights, book clubs, and many other employee-led community events. Parental Support: Balancing work and family is essential, and Scale understands the importance of having adequate leave policies in place to promote a healthy home and work life. A degree in CS, engineering, math, physics, or another quantitative fieldComfort turning ambiguous requests into structured plans with clear scope, timelines, and resource estimatesWorking fluency in the LLM training lifecycle, especially post-training: SFT, preference data, reward modeling, RL environments, evaluations, etcThe ability to read a research paper and form a view on what data would improve a given capability 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 providerExperience earning credibility with technical stakeholders through substance, and enjoying the relationship side of the workHands-on experience designing training data, evals, or RL environmentsExperience at a frontier lab, model developer, or AI data companySome customer-facing experience in pre-sales, solutions engineering, or technical consultingExperience founding a company or early-stage startup leadership experience