Member of Technical Staff, Site Reliability Engineer

📋 Job Overview

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 Inferact

We're looking for a Site Reliability Engineer to help make vLLM-powered inference systems reliable, observable, and operationally simple at production scale. This role is for someone who thinks about failure before launch, designs systems that are easier to operate, and knows how to turn incidents into durable improvements rather than one-off fixes.

🎯 The Role

You'll work across engineering and infrastructure to define SLOs, improve monitoring and alerting, strengthen incident response, drive post-mortems, and reduce operational risk before it reaches users. Your work will directly impact the reliability, availability, and production readiness of the systems powering AI inference at scale.

✅ Key Responsibilities

• Define SLOs, improve monitoring and alerting, strengthen incident response, drive post-mortems, and reduce operational risk.
• Work across engineering and infrastructure to make vLLM-powered inference systems reliable, observable, and operationally simple at production scale.
• Design systems that are easier to operate and identify likely failure modes before launch.
• Improve production systems with meaningful traffic, user impact, or infrastructure criticality.
• Live-fight major production incidents, including mitigation, root cause analysis, escalation, and follow-through on prevention work.

📌 Required Qualifications

• Bachelor's degree or equivalent experience in computer science, engineering, systems, infrastructure, or similar.
• Strong experience operating production systems with meaningful traffic, user impact, or infrastructure criticality.
• Deep understanding of SLOs, SLIs, error budgets, alerting, incident response, and post-mortem processes.
• Experience live-fighting major production incidents, including mitigation, root cause analysis, escalation, and follow-through on prevention work.
• Strong Linux, networking, systems debugging, observability, and distributed systems fundamentals.
• Ability to design operationally simple systems and identify likely failure modes before launch.
• Strong programming or scripting ability in Python, Go, Bash, or similar for automation, tooling, and reliability improvements.

⭐ Desirable Experience

• Experience supporting ML infrastructure, inference systems, GPU workloads, Kubernetes-based platforms, or high-scale backend services.
• Experience building or improving observability systems using metrics, logs, traces, dashboards, alerts, and runbooks.
• Experience with Kubernetes, Docker, Terraform, cloud infrastructure, service meshes, CI/CD systems, or production deployment platforms.
• Experience driving incident review culture, post-mortem processes, reliability reviews, and prevention-oriented engineering work.
• Ability to partner with engineering teams to improve service design, release safety, capacity planning, and operational readiness.

🎁 Benefits

Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity. We offer generous health, dental, and vision benefits as well as 401(k) company match.

🛂 Visa & Eligibility

Visa sponsorship: We sponsor visas on a case-by-case basis.