Forward Deployed Engineer - LLM Systems

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About this role

Forward Deployed Engineer - LLM Systems Menlo Park, California, United States The most important scientific discoveries of our time won't happen in a traditional lab. We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible. About the Role You will be a key builder behind the world's first on-prem LLM system for atoms, deploying inference and reinforcement learning systems directly into semiconductor fabs where the science happens. The role splits roughly 80% LLM system development and deployment, and 20% semiconductor customer interaction - translating fab requirements into engineering specs and ensuring our systems meet the realities of production. You will move fluidly between improving LLM systems, managing Kubernetes clusters, and interacting with semiconductor experts - owning deployments end-to-end and serving as the technical face of our system to vendor partners. You will also work closely with LLM systems and modeling experts from OpenAI, Anthorpic, xAI, Google, and other frontier labs. What You'll Do - Deploy and operate inference and reinforcement learning systems on-site at semiconductor partner facilities, from bring-up through ongoing operation - Build and maintain the on-prem LLM platform powering our atomic-scale science workflows, including orchestration, scheduling, observability, and reliability - Develop and extend open-source LLM frameworks (SGLang, vLLM, Megatron, Slime) to meet the performance and integration

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