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Software Engineer, Research Tools

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Software Engineer, Research Tools in USA

  • Thinking Machines Lab
  • Full time
  • Email
  • San Francisco, CA

Responsibilities

  • Design, build, and maintain research infrastructure including evaluation frameworks, training systems, experiment-tracking platforms, and visualization tools.
  • Develop end-to-end solutions across backend systems, data pipelines, and user-facing applications.
  • Partner directly with researchers to identify bottlenecks, gather feedback, prioritize work, and measure adoption.
  • Build reproducible and traceable systems with robust quality control, monitoring, and observability for research experiments and model training runs.

Requirements

  • Bachelor’s degree or equivalent practical experience in computer science, engineering, machine learning, or a related field.
  • At least two years of post-graduate software engineer or ML engineer experience, excluding internships.
  • Strong software engineering fundamentals and experience building reliable, maintainable systems.
  • Proficiency in at least one backend programming language, with Python and Rust used primarily.
  • Experience with databases, ClickHouse data warehouses, Redis or similar caching systems, and other data infrastructure.
  • Comfort working across the stack and owning projects from initial discovery through deployment and operation.
  • Experience collaborating with cross-functional partners and subject-matter experts.
  • Preferred qualifications include building researcher tools, developer productivity systems, technical products, polished user-facing applications, ML research infrastructure, or products on small teams.

Benefits

  • Generous health, dental, and vision benefits.
  • Unlimited paid time off and paid parental leave.
  • Relocation support as needed.
  • Visa sponsorship is available.
  • The role is based in San Francisco, California.

Salary: $300k - $475k/yr

Thinking Machines Lab

Thinking Machines Lab pioneers advanced AI research, blending cutting‑edge theory with practical applications to solve complex problems across industries. Our interdisciplinary team pushes the boundaries of machine learning, neural architecture, and cognitive modeling to deliver innovative soluti...

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