Research Engineer - Data and Evaluation (Fully Remote)

Prime Intellect, Inc.; United States; Teletrabalho; USD 150 000 - 350 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Quarterly off-sites

Hackathons

Conferences

Learning opportunities

Resumo da oferta

Prime Intellect is seeking researchers to work with game-changing AI teams to design RL tasks and environments for training frontier models. You will build executable setups with clear success criteria and investigate model failures to guide improvements.

The role offers remote or in-person work in San Francisco with visa sponsorship and relocation support. You will join a mission-driven team advancing open AI infrastructure with competitive compensation and opportunities to attend conferences

Responsabilidades

• Build executable environments with realistic task setup and clear success criteria.
• Trace failures through model outputs and harness code to distinguish model limitations from environment or scoring issues.
• Build and scale RL data pipelines that generate and curate challenging coding and agentic tasks.

Descrição da oferta de emprego

• Work directly with researchers to investigate model failures and design the tasks and environments that train models through RL.
• Build the evaluations that show what frontier models can actually do.

Key Responsibilities:

• Build executable environments with realistic task setup and clear success criteria.
• Trace failures through model outputs and harness code to distinguish model limitations from environment or scoring issues.
• Build and scale RL data pipelines that generate and curate challenging coding and agentic tasks.

What We Offer:

• Cash compensation range of $150-350k including equity incentives.
• Flexible work arrangements with remote or in-person options in San Francisco, plus visa sponsorship and relocation assistance.
• Quarterly off-sites, hackathons, conferences, and learning opportunities.

Prime Intellect

Prime Intellect is building the open superintelligence stack, providing infrastructure for post-training frontier AI models and open-source models trained for long-horizon tasks. The company has raised $150M from top investors and is a mission-driven team passionate about accelerating science and AI.