Site Reliability Engineer, Production at Thinking Machines Lab | CA, US | Rezi

Site Reliability Engineer, Production at Thinking Machines Lab

Site Reliability Engineer, Production

Thinking Machines Lab · CA, US

1 weeks ago

Site Reliability Engineer, Production

Thinking Machines Lab · CA, US

13 days ago
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About the Role

We're looking for a Site Reliability Engineer (SRE) 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.

Responsibilities

  • 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.

Requirements

  • 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.
  • 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.

Skills

  • distributed systems
  • cloud infrastructure
  • site reliability engineering
  • software development
  • tooling
  • automation
  • incident response
  • postmortems
  • reliability improvement
  • communication
  • coordination
  • operating production cloud services
  • distributed training frameworks
  • checkpoint and recovery systems
  • Kubernetes
  • GPU workloads

Location

  • San Francisco, California

Work Type

  • Onsite

Experience Level

  • Mid-level
  • Senior

Education Level

  • Bachelor's degree or equivalent experience

Salary/Compensations

  • $350,000 – $475,000 USD

Benefits

  • Generous health, dental, and vision benefits
  • Unlimited PTO
  • Paid parental leave
  • Relocation support
  • Visa sponsorship

About the Company

  • The mission of Thinking Machines is to build AI that extends human will and judgment.
  • We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication.
  • We believe the future worth building is human, and we're hiring people who want to build it.
  • Tinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs.
  • We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs.
  • Tinker is rapidly adding new customers, features, and novel use-cases.
  • We’re hiring to grow the platform alongside the Tinker community.