Primeintellect · San FranciscoPrepare for this interview
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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. We recently raised $15mm in funding (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. Role Impact This is a hybrid role spanning both our infrastructure layers and developer platform. You'll work on two key areas: The underlying sandbox infrastructure that powers our training systems Our developer-facing platform for AI workload management 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. Core Technical Responsibilities Infrastructure Development Design and implement distributed orchestration infrastructure in Go and Rust Build high-performance networking and coordination components Create infrastructure automation pipelines with Ansible Manage cloud resources and container orchestration Implement scheduling systems for heterogeneous hardware (CPU, GPU, TPU) Platform Development Build intuitive web interfaces for AI workload management and monitoring Develop REST APIs and backend services in Python Create real-time monitoring and debugging tools Implement user-facing features for resource management and job control Technical Requirements Infrastructure Skills Systems programming experience with Rust Strong Linux systems knowledge, including networking, namespacing, and performance tuning Virtualization experience, including VMs, hypervisors, and low-level resource management Infrastructure automation (Ansible, Terraform) Container orchestration (Kubernetes) Cloud platform expertise (GCP preferred) Observability tools (Prometheus, Grafana) Platform Skills Strong Python backend development (FastAPI, async) Modern frontend development (TypeScript, React/Next.js, Tailwind) Experience building developer tools and dashboards RESTful API design and implementation
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