Distributed AI training and inference infrastructure for custom models
Prime Intellect builds GPU infrastructure that lets organizations train and serve their own AI models, operating as both a platform and an open research lab. The stack reads like a supercomputing shop: Slurm, InfiniBand, NVLink and parallel filesystems (Lustre, BeeGFS, GPFS) alongside PyTorch, DeepSpeed, vLLM and SGLang. Hiring is accelerating and senior-heavy, concentrated in engineering and research around RL infrastructure and inference scaling.
Notable leadership hires: Strategy Finance Lead
Prime Intellect is a privately held AI infrastructure company headquartered in San Francisco with 11–50 employees. It offers a full-stack platform for training custom AI models, including agentic and reinforcement learning workloads, paired with an open research lab. Its customers are organizations that want to train their own models rather than rely solely on third-party ones. The team works across distributed training, LLM serving, GPU cluster design and a web product layer built on TypeScript, React and Next.js. Hiring is focused in the United States.
Prime Intellect runs PyTorch, DeepSpeed, vLLM, SGLang and TensorRT-LLM on CUDA, orchestrated with Ray, Slurm and Kubernetes over InfiniBand and NVLink, with Lustre, BeeGFS and GPFS storage, on GCP.
Job posts point to distributed training infrastructure, next-generation AI agents, an environments hub, an LLM serving platform, an AI workload management platform and GPU cluster architecture design.
Yes. Hiring is accelerating and engineering dominates open roles, mostly at senior level, with research roles alongside. Positions are based in the United States, with the company headquartered in San Francisco.
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Prime Intellect's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.