Research Tools Platform Engineer (ML Infra)

Thinking Machines Lab; San Francisco (CA); On-site; USD 300,000 - 475,000; Full time

Benefits offered by this job

Health, dental, and vision benefits

Unlimited PTO

Parental leave

Relocation support

Job summary

Thinking Machines is hiring to own key parts of the internal platform used to manage and monitor training runs, evaluations, and model trajectories. You will build evaluation and training libraries, experiment-tracking, and visualization tools, working closely with researchers to identify bottlenecks and deliver reliable systems.

You’ll join a small team with frequent feedback, participate in research meetings, and help define where to invest next to improve tooling for researchers.

Qualifications

• A bachelor’s degree, or equivalent practical experience, in computer science, engineering, ML, or related field.
• Two years of post-grad work experience as a software/ML engineer.
• Strong software engineering fundamentals and reliable systems.
• Proficiency in at least one backend language; Python and Rust preferred; frontend with React/Typescript.
• Experience with databases, data warehouses (ClickHouse), caching systems like Redis.
• Able to own projects from discovery through deployment and operation.
• Experience collaborating with cross-functional partners.

Responsibilities

• Design, build, and maintain research infra, including evaluation frameworks, training systems, experiment tracking platforms, and visualization tools.
• Work across backend systems, data pipelines, and user-facing applications to deliver tools end to end.
• Partner with researchers to identify bottlenecks and unlock new capabilities; treat tooling as a product.
• Build systems for reproducibility, traceability, and high quality with monitoring.

Skills

Backend programming

Python

Rust

React

Typescript

Databases

Redis caching

System design

Cross-functional teamwork

Education

Bachelors in CS/Engineering

Tools

ClickHouse

Redis

Data warehouses

Job description

Thinking Machines is hiring to own key parts of the internal platform used to manage and monitor training runs, evaluations, and model trajectories. You will build evaluation and training libraries, experiment-tracking, and visualization tools, working closely with researchers to identify bottlenecks and deliver reliable systems.

You’ll join a small team with frequent feedback, participate in research meetings, and help define where to invest next to improve tooling for researchers.