Thinking Machines Lab

Thinking Machines Lab

Engineering Manager

San Francisco

H1B sponsorship available$400k-$500kDetected 55 days ago
Machine LearningPyTorchLogisticsSystems EngineeringCollaboration

About the role

  • This role combines collaboration with hand-on work.

Responsibilities

  • Lead and grow a team of senior and staff-level engineers, setting clear expectations and maintaining a high bar for execution.
  • Own architecture, system design, and long-term technical direction for your team's systems, with emphasis on reliability and performance.
  • Contribute directly to design reviews, prototyping, and debugging critical issues.
  • Partner with researchers and product teams to define roadmaps and prioritize work.

Requirements

  • Bachelor's degree or equivalent industry experience in computer science, engineering, or similar.
  • 8+ years of experience building and scaling production systems, including system design and distributed systems.
  • 3+ years of engineering management experience in high-growth environments.

Nice to have

  • we encourage you to apply even if you don't meet all preferred qualifications, but at least some:
  • Experience managing teams of senior or staff-level engineers.
  • Background in infrastructure, systems engineering, or developer productivity.
  • Familiarity with AI/ML systems, data infrastructure, or high-performance computing.

Skills

  • Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence.

Compensation

  • Depending on background, skills and experience, the expected annual salary range for this position is $400,000 - $500,000 USD.

Benefits

  • Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

Visa & Work Authorization

  • 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.
  • We sponsor visas.

This listing is sourced directly from Thinking Machines Lab's careers page and normalized into a canonical job model.