Frontier AI Data Strategist

Scale AI; New York (NY); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health & wellbeing benefits

Career growth stipends

Community & events

Job summary

Scale AI is seeking a Frontier Data Strategist to shape data programs for frontier research. You will work with researchers and Scale teams to translate research directions into concrete data requirements, specs, and scope, guiding product priorities and investments.

You will engage with leading labs, forecast opportunities, and price engagements while building strong technical relationships and guiding data-driven roadmap decisions.

Qualifications

• 3+ years in a technical AI/ML role such as ML engineering, research, applied science, or technical product management.
• Hands-on experience designing training data, evals, or RL environments.
• Experience earning credibility with technical stakeholders.
• Some customer-facing experience in pre-sales, solutions engineering, or technical consulting.

Responsibilities

• Design human-data programs (task design, data specs, quality bars, expert profiles) to turn research goals into concrete projects.
• Forecast, scope and price opportunities; win work and hand off to Delivery Operations.
• Match customer needs to Scale’s product roadmap with AI product managers and ML teams.
• Build trusted relationships with frontier labs and act as a technical thought partner on post-training evaluation and agent work.

Skills

AI/ML experience

Customer-facing

Pre-sales experience

Research paper reading

Education

CS/Engineering/Math/Physics degree

Tools

LLM training lifecycle

Job description

Scale AI is seeking a Frontier Data Strategist to shape data programs for frontier research. You will work with researchers and Scale teams to translate research directions into concrete data requirements, specs, and scope, guiding product priorities and investments.

You will engage with leading labs, forecast opportunities, and price engagements while building strong technical relationships and guiding data-driven roadmap decisions.