Member of Technical Staff, Performance and Scale
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At a glance
Requirements
Credentials this posting asks for.
Job overview
Inferact is hiring a Member of Technical Staff, Performance and Scale. Inferact seeks an infrastructure engineer to design and implement distributed systems that power AI inference at global scale, building foundational layers for low‑latency, high‑reliability model serving across thousands of accelerators, aiming to make large‑scale deployment as simple as a serverless database.
Key focus areas include Design and implement foundational layers for distributed AI inference, Build high‑performance distributed systems that scale across thousands of accelerators, and Ensure minimal latency and maximum reliability for model serving.
Successful candidates bring Bachelor's Degree Or Equivalent In Computer Science, Engineering, Or Similar, Strong Systems Programming Skills, and Experience Designing And Building High-Performance Distributed Systems At Scale. Important skills include Rust, Go, C++, Designing Distributed Systems, Implementing Distributed Systems, and Network Protocols. Preferred (not required): ML Serving Infrastructure, Disaggregated Inference Architecture, GPU Programming Models, and Memory Hierarchies.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware—a position that took years to build.
About the Role We're looking for an infrastructure engineer to build the distributed systems that power inference at global scale. You'll design and implement the foundational layers that enable vLLM to serve models across thousands of accelerators with minimal latency and maximum reliability. Tomorrow, deploying a frontier model at scale should be as straightforward as spinning up a serverless database. The complexity doesn't disappear as it gets absorbed into the infrastructure you're building.
Skills and Qualifications Minimum qualifications:
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Bachelor's degree or equivalent experience in computer science, engineering, or similar.
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Strong systems programming skills in Rust, Go, or C++.
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Experience designing and building high-performance distributed systems at scale.
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Understanding of network protocols and high-performance I/O.
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Ability to debug complex distributed systems issues.
Preferred qualifications:
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Experience with ML serving infrastructure and disaggregated inference architecture.
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Familiarity with GPU programming models and memory hierarchies.
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Knowledge of GPU interconnects (NVLink, InfiniBand, RoCE) and their performance characteristics.
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Track record of improving system reliability and performance at scale.
Bonus points if you have:
- Prior experience in supporting large‑scale model training or inference environments.
Logistics
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Location: This role is based in San Francisco, California. Will consider remote in the US for exceptional candidates.
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Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.
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Visa sponsorship: We sponsor visas on a case-by-case basis.
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Benefits : Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.
You've read the whole posting — now see how you match it.