Site Reliability Engineer (SRE)

Thinking Machines Lab

$350K — $475K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree or equivalent in computer science, engineering, or similar field.
  • Experience in distributed systems, cloud infrastructure, or site reliability engineering.
  • Proficiency in writing software for reliability solutions, including tooling and automation.
  • Background in production incident response and conducting postmortems for reliability improvement.
  • Strong communication skills for effective coordination with engineering and research teams.

Responsibilities

  • Define and own end-to-end reliability from CI/CD to incident response.
  • Develop Service Level Objectives for distributed training systems balancing reliability and speed.
  • Design and implement monitoring for the entire training path.
  • Lead incident response for Tinker platform, ensuring rapid recovery and improvements.
  • Enhance multi-tenant isolation and resource scheduling for LoRA workloads.
  • Collaborate with security teams to address production vulnerabilities.

Benefits

  • Generous health, dental, and vision coverage.
  • Unlimited PTO policy.
  • Paid parental leave provided.
  • Relocation support available as needed.
Full Job Description
About the Role

We're looking for a Site Reliability Engineer to drive the reliability of Tinker end-to-end. You'll work alongside the engineers building the platform and research teams to make every layer of the system more robust and resilient.

What You'll Do
  • Define and own end-to-end reliability, from CI/CD flows to production observability and incident response.
  • Develop appropriate Service Level Objectives for distributed training systems, balancing job completion reliability and scheduling latency with development velocity.
  • Design and implement monitoring and observability across the full training path.
  • Drive incident response for Tinker platform issues, ensuring rapid recovery, thorough incident reviews, and systematic improvements that prevent recurrence.
  • Harden multi-tenant isolation and resource scheduling so that LoRA-based workload co-scheduling maximizes utilization without compromising reliability or data separation
  • Collaborate with security teams to address production vulnerabilities
Skills and Qualifications

Minimum qualifications:
  • Bachelor's degree or equivalent experience in computer science, engineering, or similar.
  • Experience in distributed systems, cloud infrastructure, or site reliability engineering.
  • Proficiency writing software to solve reliability problems, including building tooling and automation.
  • Experience with production incident response, postmortems, and systematic reliability improvement.
  • Strong communication skills and track record of coordination across engineering and research teams.

Preferred qualifications - we encourage you to apply if you meet some but not all of these:
  • Deep experience operating production cloud services at scale (e.g., public cloud platforms, internal cloud services)
  • Background in distributed training frameworks and how infrastructure failures surface in training behavior.
  • Track record building checkpoint and recovery systems for long-running distributed jobs.
  • Expertise in Kubernetes at scale: deploying, operating, debugging, and tuning clusters handling heterogeneous GPU workloads.
Logistics
  • Location: This role is based in San Francisco, California.
  • Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
  • Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
  • Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

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