Prime Intellect · San Francisco, United States, US · 11 days ago
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.
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.
You will work on a distributed system with performance engineering at its core. The role will draw on the full breadth of your systems skills, from deep Linux kernel topics to high-level distributed system design. Expect your low-level systems fortitude to be pushed as you build infrastructure that remains fast, robust, and reliable at scale.
You'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.
We value potential over perfection - if you're passionate about democratizing AI development and have experience in either platform or infrastructure development (ideally both), we want to talk to you.
Ready to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone.
Headquarters
San Francisco, United States
Work Location
hybrid
Job Category
Software Development
Application Deadline
Not specified
Job Type
Full Time
Experience Level
lead
Application Method
Apply via Website
Salary
150k - 300k USD/year
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