Research Engineer - Reinforcement Learning at Prime Intellect

**Who this is for** Prime Intellect is looking for a Research Engineer specializing in Reinforcement Learning to join their Reasoning team. This role is ideal f

Work type: remote

Location: San Francisco | Remote

Salary: $150,000 – $300,000/yr

Type: Full-time

Summary

**Who this is for** Prime Intellect is looking for a Research Engineer specializing in Reinforcement Learning to join their Reasoning team. This role is ideal for individuals passionate about synthetic data generation and teaching LLMs reasoning abilities, with a strong background in AI/ML engineering. **Key highlights** You will lead research for a large-scale synthetic data generation pipeline, optimize AI inference workloads for performance and cost, and contribute to open-source libraries. This position offers the opportunity to publish at top AI conferences and make a significant impact on the future of decentralized AI. **You might be a good fit if you...** - Have extensive experience in designing and implementing end-to-end pipelines for large-scale AI model inference or training. - Possess deep expertise in distributed inference techniques and frameworks (e.g., vllm, sglang). - Have a solid understanding of MLOps best practices. - Are passionate about advancing the state-of-the-art in reasoning and democratizing AI access.

Job Description

Building Open Superintelligence Infrastructure

Prime Intellect is building the open superintelligence stack - from frontier agentic models to the infra that enables anyone to create, train, and deploy them. We aggregate and orchestrate global compute into a single control plane and pair it with the full rl post-training stack: environments, secure sandboxes, verifiable evals, and our async RL trainer. We enable researchers, startups and enterprises to run end-to-end reinforcement learning at frontier scale, adapting models to real tools, workflows, and deployment contexts.

As a Research Engineer in our Reasoning team, you'll play a crucial role in shaping our technological direction, focusing on our test-time compute scaling research ideas. If you love working with synthetic data and teach LLMs reasoning abilities, this role is for you.
For more details about the project you would be working on, check out our [outlook on decentralized training in the inference-compute paradigm.](https://www.primeintellect.ai/blog/intellect-math)

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## Benefits & Perks






We recently raised [$15mm in funding](https://www.primeintellect.ai/blog/fundraise) (total of $20mm raised) led by Founders Fund, with participation from Menlo Ventures and prominent angels including Andrej Karpathy (Eureka AI, Tesla, OpenAI), Tri Dao (Chief Scientific Officer of Together AI), Dylan Patel (SemiAnalysis), Clem Delangue (Huggingface), Emad Mostaque (Stability AI) and many others.

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.

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