Member of Technical Staff, Performance and Scale
- Pay
- $200,000 – $400,000 per year
- Location
- San Francisco, CA · On-site
- Job type
- Full-time
- Level
- Mid-level
- Education
- Bachelor's degree
- Listed
- 31 days ago
Skills & highlights for this role
- Rust
- Go
- distributed systems
Also useful
- GPU programming
- NVLink
- InfiniBand
Stated benefits & perks
- Health
- Dental
- Vision
- 401k match
About the role
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.
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.
From Inferact's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
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Common questions
What is the salary for the Member of Technical Staff, Performance and Scale role at Inferact?
The Member of Technical Staff, Performance and Scale posting at Inferact states compensation of $200,000 – $400,000 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on Inferact's official career site.
Where is the Member of Technical Staff, Performance and Scale job at Inferact located?
This Member of Technical Staff, Performance and Scale position at Inferact is located in San Francisco, CA (On-site). Always check Inferact's application page for specific state eligibility or relocation policies.
What qualifications are required for Member of Technical Staff, Performance and Scale at Inferact?
For the Member of Technical Staff, Performance and Scale role, Inferact highlights a bachelor's degree; experience with Rust, Go, distributed systems. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Member of Technical Staff, Performance and Scale position at Inferact?
This listing links directly to Inferact's Ashby application page. You can apply directly on Inferact's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.