Inferact
Member of Technical Staff, Production Site Reliability Engineer
San Francisco · Staff+
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odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$21,187 more — $221,187 — moves this role to Level IV and 4 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $221,187 would place this position at wage Level IV. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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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.
- We're looking for a Site Reliability Engineer to make Inferact's vLLM-powered inference services dependable in production.
- This is a hands-on engineering role for someone who thinks about failure before launch, simplifies operations, and writes software that makes reliable inference possible at scale.
Responsibilities
- You'll help own reliability across the production lifecycle, from release safety and observability to incident response and recovery. You'll define SLOs around availability, latency, and successful inference requests
- build monitoring that helps engineers pinpoint failures
- When incidents occur, you'll drive mitigation, coordinate escalation, and lead post-mortems that result in concrete prevention work.
- You'll also partner with engineering on capacity planning and operational readiness so the platform can grow without becoming harder to operate.
- You'll help own reliability across the production lifecycle, from release safety and observability to incident response and recovery.
- You'll define SLOs around availability, latency, and successful inference requests; build monitoring that helps engineers pinpoint failures; and automate recurring operational work.
Requirements
- Bachelor's degree or equivalent experience in computer science, engineering, systems, infrastructure, or similar.
- Experience responding to significant production incidents, including mitigation, root cause analysis, escalation, and following corrective actions through to completion.
- Strong Linux, networking, and systems debugging fundamentals, with the ability to investigate failures across application and infrastructure boundaries.
- Clear communication, sound judgment under pressure, and the ability to work with engineering teams to identify failure modes and make systems simpler to operate.
Nice to have
- Experience supporting AI inference, model serving, ML infrastructure, GPU workloads, or other latency-sensitive, high-throughput services.
- Experience deploying, operating, and debugging Kubernetes-based services, with familiarity with Docker, Terraform, or comparable infrastructure tooling.
- Experience improving deployment safety and recovery through automation, testing, release gates, and rollback procedures.
- Experience with resource scheduling, capacity planning, or workload isolation in multi-tenant cloud or GPU environments.
- Owned reliability for an inference service or other mission-critical platform through a period of significant growth.
- Built automation that measurably reduced operational toil, improved recovery time, or prevented repeat incidents.
- Established practical SLOs, post-mortem processes, or production-readiness reviews that helped engineering teams ship with greater confidence.
- Visa sponsorship: We sponsor visas on a case-by-case basis.
Skills
- Skills and Qualifications
Compensation
- Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.
Benefits
- We offers generous health, dental, and vision benefits as well as 401(k) company match.
Company info
- About the Role We're looking for a Site Reliability Engineer to make Inferact's vLLM-powered inference services dependable in production.
- 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.
Visa & Work Authorization
- We sponsor visas on a case-by-case basis.
This listing is sourced directly from Inferact's careers page and normalized into a canonical job model.