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About the Role
Prime Intellect is building the open superintelligence stack, providing infrastructure for ambitious AI teams. Their platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for post-training at frontier scale. They are developing open frontier AI, including open-source models and a full-stack platform for AI development. The company has raised $150M and seeks individuals passionate about building at the intersection of frontier research, real infrastructure, and go-to-market strategy.
Responsibilities
- Own applied RL programs from customer problem identification through deployed improvement loops.
- Understand workflow and business stakes to define measurable outcomes and learning objectives.
- Build environments and evaluations for post-training experiments.
- Run post-training experiments, deploy results, and generalize findings into Prime's shared stack.
- Work directly with customer researchers, engineers, and leaders, ensuring research results and practical impact.
- Turn workflows into tasks, environments, evaluations, and reward signals.
- Run post-training experiments against real baselines and deploy successful solutions.
- Determine if gains are from model, data, harness, inference, or infrastructure.
- Convert reusable components into shared research, open-source systems, and product capabilities.
- Work directly with customers, users, or research partners while maintaining a research agenda.
- Improve domain agents using RL or other post-training methods, distinguishing model limitations from other failures.
- Carry successful experiments into deployment, measure impact, and convert recurring elements into reusable assets.
- Conduct technical and business discovery to define research plans, success measures, environments, and baselines.
- Execute RL, distillation, and other post-training experiments tied to deployment outcomes.
- Develop agent systems for tool use, memory, recovery, long horizons, and human oversight.
- Make deployment and adoption decisions, and contribute reusable artifacts to Prime's teams.
Requirements
- Relevant experience in customer-embedded technical work, research engineering, technical founding, applied ML consulting with build ownership, or end-to-end post-training programs.
- Comfortable engaging with senior external teams and connecting experimental evidence to business decisions without compromising research standards.
- Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely related experimental loops.
- Strong experimental judgment, including establishing meaningful baselines, careful trace inspection, clear failure attribution, and adaptability based on evidence.
- Proficiency in Python and the ability to create artifacts runnable, inspectable, and extendable by other researchers and engineers.
- Comfort owning ambiguous problems and maintaining clear communication with partners and teammates.
- Evidence of exceptional work through publications, open-source systems, benchmarks, or shipped products.
- Ability to articulate difficult projects, failures, and adaptive approaches.
Skills
- Applied RL
- Post-training methods
- Agent systems
- Tool use
- Memory management
- Recovery mechanisms
- Long horizon tasks
- Human oversight
- Python
Location
- San Francisco
- New York
- London
- Remote
Work Type
- Full-time
- Remote
Experience Level
- Senior
Salary/Compensations
- $150-300k
Benefits
- Cash Compensation Range of $150-300k + equity incentives
- Flexible Work
- Visa Sponsorship & relocation support
- Professional Development budget
- Team Off-sites & conference attendance
About the Company
- Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
- Their platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale.
- They are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform their own research team uses to build them.
- Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators.
- They are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.