Lead Applied Researcher

Own Your Intelligence

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators, including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We 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.

Role Impact

Lead an Applied Research team that makes models work on difficult customer tasks. Stay hands-on with RL experiments and take useful results through to deployment. Set the team’s priorities and decide where to spend its compute. This is a tech lead manager role, based in New York or San Francisco.

Responsibilities

Applied Research at Prime

We turn a workflow into tasks, environments, evaluations, and reward signals, run post-training experiments against real baselines, and deploy what works. When a result looks good, we find out whether the gain came from the model or from the data, harness, inference, or infrastructure. The reusable parts become shared research, open-source systems, and product capabilities.

Every Applied Research role is externally facing. Most researchers work directly with customers, users, or research partners while maintaining a substantive research agenda.

Role scope

This is a leadership role within Prime's broader Applied Research function, based in New York or San Francisco. It requires research taste, technical depth, customer and partner judgment, exceptional recruiting, and the willingness to remain a builder. Reporting to our Head of Applied Research, you will stay directly involved with external program teams while leading technical work, recruiting, and developing the group.

Representative early problems

• Turn a portfolio of field programs into research agendas with strong owners, comparable evidence, and explicit paths from domain result to shared capability.

• Personally lead a high-stakes program through environment design, baseline, post-training, evaluation, and deployment while establishing the quality bar for the growing team.

• Recruit researchers and establish a working rhythm that keeps review rigorous without slowing the team.

What you will own

• A small number of the hardest partner and customer research programs.

• Recruiting and development of the Applied Research department, including direct people management.

• Technical standards for environments, evaluations, post-training experiments, failure analysis, and deployed results.

• Meaningful personal research, cross-program technical direction, and decisions about what becomes shared research or product capability as the team grows.

• Program priorities and allocation of clusters and compute across the team's RL experiments.

Requirements

• You’ve led an applied research or research engineering team while continuing to do technical work.

• You’ve run and debugged RL experiments yourself. You can explain what went wrong in a run and how you fixed it.

• You can defend an experimental result. You know when a better score comes from learning and when it comes from a broken evaluation.

• You know how to prioritize work across a team and explain tradeoffs to demanding customers.

• You write strong Python. Other researchers can run and extend what you build.

Useful background

• Around 6-8 years of relevant research or engineering work, with recent hands-on ownership.

• Experience at both a larger technology organization and a startup. We’re looking for disciplined management alongside the speed to build with a small team.

Evidence of exceptional work

Publications, open-source systems, benchmarks and shipped products can all be evidence. Show us difficult work you personally owned, and what you learned when it failed.

Benefits and Perks

• Cash Compensation Range of $150-300k + equity incentives

• Full medical, dental and vision coverage for employees and dependents.

• Flexible PTO.

• $200/month health and wellness benefit.

• Visa sponsorship and relocation support.

• Professional development budget for courses and conferences.

• Team off-sites and conference attendance.

• Company-covered meals when working from our San Francisco office.

If you're excited about the opportunity to build the foundation for the future of decentralized AI and create a platform that empowers developers and researchers to push the boundaries of what's possible, we'd love to hear from you.