Train, deploy, and continuously improve your own models on an integrated compute, training, inference, and sandbox stack. Backed by Menlo.
About the role
Help develop the algorithms and systems used to train Prime Intellect’s open models with reinforcement learning. We’re hiring research engineers and scientists across RL algorithms, scaling research, and training frameworks. Your focus will reflect your strengths; you don’t need to cover all three. Demonstrated depth in at least one of RL algorithms, empirical research on model training, or distributed ML systems. This could come through research, open-source contributions, or systems you’ve built. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Demonstrated depth in at least one of RL algorithms, empirical research on model training, or distributed ML systems. This could come through research, open-source contributions, or systems you’ve built
- Strong programming skills in Python and experience with PyTorch or a comparable ML framework
- Ability to design controlled experiments, interpret results, and debug unexpected model or system behavior
- Experience taking a research idea or systems change through implementation, testing, and evaluation, with a clear account of what worked and what didn’t
More about this role
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,...
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