Member of Technical Staff, Performance and Scale

Inferact; San Francisco (CA); On-site; USD 200,000 - 400,000; Full time

Benefits offered by this job

Generous health benefits

Dental and vision benefits

401(k) company match

Job summary

A tech company is seeking an infrastructure engineer to design and implement distributed systems for AI inference in San Francisco, California. The role requires strong programming skills in Rust, Go, or C++, and experience in building high-performance systems at scale. Compensation ranges from $200,000 to $400,000 per year plus equity. Exceptional remote candidates will also be considered. The company offers generous health benefits and a 401(k) match.

Qualifications

• Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
• Strong systems programming skills in Rust, Go, or C++.
• Experience designing and building high-performance distributed systems at scale.
• Understanding of network protocols and high-performance I/O.
• Ability to debug complex distributed systems issues.

Responsibilities

• Build distributed systems that power inference at global scale.
• Design and implement foundational layers for model serving.
• Ensure minimal latency and maximum reliability for deployed models.

Skills

Rust

Go

C++

Systems programming

Distributed systems

Network protocols

High-performance I/O

Education

Bachelor's degree in computer science or engineering

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:

• Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
• Strong systems programming skills in Rust, Go, or C++.
• Experience designing and building high-performance distributed systems at scale.
• Understanding of network protocols and high-performance I/O.
• Ability to debug complex distributed systems issues.

Preferred qualifications:

• Experience with ML serving infrastructure and disaggregated inference architecture.
• Familiarity with GPU programming models and memory hierarchies.
• Knowledge of GPU interconnects (NVLink, InfiniBand, RoCE) and their performance characteristics.
• 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

• Location: This role is based in San Francisco, California. Will consider remote in the US for exceptional candidates.
• Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 – $400,000 USD + equity.
• Visa sponsorship: We sponsor visas on a case‑by‑case basis.
• Benefits: Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.

Compensation Range: $200K – $400K