Member of Technical Staff, Performance and Scale

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

Benefits offered by this job

Generous health, dental, and vision benefits

401(k) company match

Equity options

Job summary

A leading AI technology company located in San Francisco is seeking an infrastructure engineer to build distributed systems for their AI inference engine. The role involves designing systems that ensure minimal latency and maximum reliability. Candidates should have a strong background in systems programming (Rust, Go, C++) and experience with distributed systems. The compensation ranges from $200,000 to $400,000 USD annually, accompanied by benefits and possible visa sponsorship.

Qualifications

• Bachelor's degree or equivalent in computer science or engineering.
• Strong systems programming skills in Rust, Go, or C++.
• Experience with high-performance distributed systems.
• Understanding of network protocols and the ability to debug issues.

Responsibilities

• Design and implement systems that power inference at global scale.
• Enable vLLM to serve models across thousands of accelerators.
• Absorb complexity into the infrastructure being built.

Skills

Systems programming skills in Rust, Go, or C++

Designing and building high-performance distributed systems

Understanding of network protocols and high-performance I/O

Ability to debug complex distributed systems issues

Education

Bachelor's degree or equivalent experience in computer science, engineering, or similar

Tools

GPU programming models

NVLink

InfiniBand

RoCE

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