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Role Impact:
- 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.