Member of Technical Staff, Performance and Scale

Benefits

Parental leave

Not verified

Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$200K-$400K From the posting source checked Jun 20, 2026

401(k) match

Reported not verified - source not recorded; source URL not recorded; timestamp not recorded

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

157% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Staff Plus From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Company

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Member of Technical Staff, Performance and Scale San Francisco, California, United States 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

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