Software Engineer, Research Tools
Thinking Machines Lab1 month ago
Base Salary
$300k - $475k/yr
Responsibilities
- Design, build, and maintain research infrastructure including evaluation frameworks, training systems, experiment-tracking platforms, and visualization tools.
- Develop solutions across backend systems, data pipelines, and user-facing applications.
- Partner directly with researchers to identify bottlenecks, gather feedback, prioritize work, and unlock new capabilities.
- Build reproducible, traceable, reliable research systems with robust quality control, monitoring, and observability.
- Own projects from problem discovery through deployment and operation.
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 experience as a software engineer or ML engineer, excluding internships.
- Strong software engineering fundamentals and experience building reliable, maintainable systems.
- Proficiency in at least one backend programming language, particularly Python or Rust, plus familiarity with React and TypeScript for frontend work.
- Experience with databases, data warehouses such as ClickHouse, caching systems such as Redis, and other data infrastructure.
- Ability to work across the stack and collaborate with cross-functional partners and subject-matter experts.
- Preferred qualifications include experience building researcher tools, developer productivity tools, technical products, polished user-facing applications, ML research infrastructure, or products on small teams.
Benefits
- San Francisco, California-based role.
- Visa sponsorship is available.
- Health, dental, and vision benefits.
- Unlimited paid time off and paid parental leave.
- Relocation support as needed.
Tech Stack
Categories
Data EngineeringFull Stack
About Thinking Machines Lab
Thinking Machines Lab develops AI and generative AI software and conducts applied research to help organizations make data-driven decisions. The company builds products and data science solutions for enterprise use cases, pairing foundational models with practical tooling and services across industries. It is privately held and headquartered in San Francisco.