SambaNova Systems

Technology

SeniorSoftwareEngineer,MLInfrastructure

$175–275k ~AI est. United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“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.

Technology
Problems you'll solve

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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