Nova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of Samba
Nova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into Samba
Rack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. About the Team The ML Infrastructure team builds and operates the inference stack that serves Samba
Nova's models on our RDU accelerators. We cover request scheduling, caching, decoding techniques, public APIs, and the accuracy testing that every inference feature must pass before it ships. About the Role As a new grad ML Infrastructure Engineer, you'll write production Python for our inference serving stack, including our vLLM integration and public APIs.
You'll help bring features like speculative decoding, prompt caching, and tool calling into production on the RDU, and add accuracy and regression tests that catch problems before customers do.
Implement inference features on the RDU such as speculative decoding, constrained decoding, tool calling, prompt caching, and long-context inference Adapt vLLM and related serving frameworks to the RDU architecture Buil