Senior ML Infrastructure Engineer - Remote

Originally posted 4 June 2026 by the employer.

Build and operate production-grade inference systems on SambaNova's Reconfigurable Dataflow Unit (RDU) architecture.

About the role

The Senior ML Infrastructure Engineer is responsible for designing, building, and operating the production-grade inference infrastructure that powers SambaNova's serving stack on the Reconfigurable Dataflow Unit (RDU) architecture. The role focuses on taking inference techniques from prototype to production and building systems spanning request scheduling, advanced decoding algorithms, caching layers, and public API surfaces.

What you'll do

- Design and productionize advanced inference techniques on RDU to optimize for performance and cost, including speculative decoding, constrained decoding, function/tool calling, prompt caching, and long-context inference. - Own SambaNova's integration with vLLM and adjacent serving frameworks, adapting them to the RDU architecture. - Own the public inference API surface exposed through SambaStack and SambaCloud. - Build and maintain the accuracy verification and regression infrastructure that gates every inference feature shipped to customers. - Partner with ML, compiler, runtime, and product teams to take inference features from prototype to production. - Contribute to technical design discussions, code reviews, and architectural decisions as a senior individual contributor.

What you'll need

- B.S. in Computer Science, Electrical Engineering, or a related field. - 5+ years of industry experience building and operating large-scale distributed systems, ideally in ML serving. - Strong software engineering fundamentals: algorithms, data structures, concurrency, and systems design. - Experience designing and maintaining production services with strict latency, throughput, and availability requirements. - Working knowledge of modern LLM inference techniques and familiarity with open-source serving stacks such as vLLM, TensorRT-LLM, or SGLang. - Proficiency in Python. - Experience collaborating across teams to deliver complex, system-level engineering solutions.

Skills: ML infrastructure, production-grade inference, distributed systems, LLM inference, SambaNova's RDU