SambaNova Systems
Technology
SeniorSoftwareEngineer,MLInfrastructure
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer, ML Infrastructure at SambaNova Systems. Skills: ML Infrastructure, Inference serving, Distributed systems. Design advanced inference techniques on RDU. Productionize advanced inference techniques on RDU”
What You'll Achieve.
Optimize for performance and cost; Ship inference features from prototype to production
Industry & Context.
Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, 5+ years of industry experience, Experience building and operating large-scale distributed systems, Experience in ML serving software engineering fundamentals, Experience designing and maintaining production services, Working knowledge of modern LLM inference techniques, Proficiency in Python, Experience collaborating across teams
Nice to Have
Experience in ML serving software engineering fundamentals: algorithms, Experience in ML serving software engineering fundamentals: data structures, Experience in ML serving software engineering fundamentals: concurrency, Experience in ML serving software engineering fundamentals: systems design, Familiarity with open-source serving stacks such as vLLM, Familiarity with open-source serving stacks such as TensorRT-LLM, Familiarity with open-source serving stacks such as SGLang
What You'll Do.
Design advanced inference techniques on RDU
Productionize advanced inference techniques on RDU
Optimize for performance and cost
Own SambaNova's integration with vLLM
Adapt vLLM to RDU's architecture
Own the public inference API surface
Build accuracy verification infrastructure
Maintain accuracy verification infrastructure
Gate inference features shipped to customers
Partner with ML teams
Partner with compiler teams
Partner with runtime teams
Partner with product teams
Take inference features from prototype to production
Contribute to technical design discussions
Contribute to code reviews
Contribute to architectural decisions
How You'll Work.
Team & Collaboration
Partner with ML teams; Partner with compiler teams; Partner with runtime teams; Partner with product teams
Full Job Description
The era of pervasive AI has arrived. In this era, organizations will use generative AI to unlock hidden value in their data, accelerate processes, reduce costs, drive efficiency and innovation to fundamentally transform their businesses and operations at scale. SambaNova Suite™ is the first full-stack, generative AI platform, from chip to model, optimized for enterprise and government organizations. Powered by the intelligent SN40L chip, the SambaNova Suite is a fully integrated platform, delivered on-premises or in the cloud, combined with state-of-the-art open-source models that can be easily and securely fine-tuned using customer data for greater accuracy. Once adapted with customer data, customers retain model ownership in perpetuity, so they can turn generative AI into one of their most valuable assets. Overview The Senior Software Engineer, ML Infrastructure will be responsible for designing, building, and operating the production-grade inference infrastructure that powers SambaNova's serving stack on our Reconfigurable Dataflow Unit (RDU) architecture. SambaNova is an inference-first company, and this role sits at the heart of that mission: turning state-of-the-art inference techniques into reliable, high-throughput, low-latency services exposed to customers through SambaStack and SambaCloud. The engineer will own end-to-end systems spanning request scheduling, advanced decoding algorithms, caching layers, API surfaces, and the accuracy infrastructure that keeps the stack trustworthy. This role partners closely with ML, compiler, runtime, and product teams to ship inference features from prototype to production. Qualifications Bachelor's degree in Computer Science, Electrical Engineering, or 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 producti
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