Job description

ABOUT THINKING MACHINES 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. ABOUT THE ROLE Evaluation is one of the most important pillars of building frontier AI systems. It guides research direction, powers experimentation, and helps us understand whether changes to data and training are improving the capabilities and behaviors we care about. To support this work, researchers need a powerful, self-serve platform that makes it easy to author evaluations, run them or reproduce them reliably at scale, and extract insight from the results. The platform must support both standardized external benchmarks and fast-moving internal evaluations, many kinds of tasks and graders, and inspection from aggregate metrics down to individual model trajectories. In this role, you will design and build this platform end to end. You will work across Python frameworks, data pipelines, APIs, and user-facing applications, and collaborate closely with pre-training, post-training, and applied teams to improve how we evaluate models and turn results into research decisions. WHAT YOU'LL DO - Design, build, and maintain the platform for authoring, running, tracking, and analyzing model evaluations that are critical in day to day work and model releases. - Work across evaluation libraries, distributed backend systems, data pipelines, APIs, and user-facing applications to deliver capabilities end to end. - Build flexible abstractions for evaluation tasks, environments, graders, datasets, and model outputs without constraining fast-moving research. - Make evaluation results reproducible and trustworthy through versioning, provenance, observability, failure recovery, and robust quality controls. - Partner directly with researchers to identify bottlenecks and turn bespoke workflows into self-serve systems that work across teams. - Work with Research Tooling, the engineering team behind Thinking Machines’ internal research platform. SKILLS AND QUALIFICATIONS MINIMUM QUALIFICATIONS - A bachelor’s degree, or equivalent practical experience, in computer science, engineering, machine learning, or a related field. - Two years of post-grad work experience as a software engineer or ML engineer, exclusive of internships. - Hands-on experience building or maintaining evaluations, benchmarks, graders, or model-quality systems for large language or multimodal models. - Strong software engineering fundamentals and experience building reliable, maintainable systems. - Proficiency in at least one backend programming language; we primarily use Python and Rust. We use React and Typescript on the frontend. - Experience with databases, data pipelines, distributed systems, or other data-intensive infrastructure. - Comfort working across the stack and owning projects from initial problem discovery through deployment and operation. - Experience collaborating with cross-functional partners and subject-matter experts. PREFERRED QUALIFICATIONS We encourage you to apply even if you meet only some of these: - A track record of building frameworks, SDKs, or developer tools with thoughtful abstractions and a strong user experience. - Experience with distributed job execution, workflow orchestration, sandboxed environments, or large-scale data processing. - Experience building polished, intuitive interfaces for inspecting complex data, comparing experiments, or debugging model behavior. - Familiarity with large language or multimodal model evaluation, including model-based grading, human evaluation, or synthetic data. - Experience working closely with researchers to understand their workflows and turn rapidly evolving needs into durable systems. - Experience at a startup or on a small team, building technically complex products end to end. LOGISTICS - Location: This role is based in San Francisco, California. - Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $300,000 - $350,000 USD. - Visa sponsorship: We sponsor visas. 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. - Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

Requirements

Must-haves

Design, build, and maintain the platform for authoring, running, tracking, and analyzing model evaluations that are critical in day to day work and model releases.
Work across evaluation libraries, distributed backend systems, data pipelines, APIs, and user-facing applications to deliver capabilities end to end.
Build flexible abstractions for evaluation tasks, environments, graders, datasets, and model outputs without constraining fast-moving research.
Make evaluation results reproducible and trustworthy through versioning, provenance, observability, failure recovery, and robust quality controls.
Partner directly with researchers to identify bottlenecks and turn bespoke workflows into self-serve systems that work across teams.
Work with Research Tooling, the engineering team behind Thinking Machines’ internal research platform.
A bachelor’s degree, or equivalent practical experience, in computer science, engineering, machine learning, or a related field.
Two years of post-grad work experience as a software engineer or ML engineer, exclusive of internships.
Hands-on experience building or maintaining evaluations, benchmarks, graders, or model-quality systems for large language or multimodal models.
Strong software engineering fundamentals and experience building reliable, maintainable systems.
Proficiency in at least one backend programming language; we primarily use Python and Rust. We use React and Typescript on the frontend.
Experience with databases, data pipelines, distributed systems, or other data-intensive infrastructure.
Comfort working across the stack and owning projects from initial problem discovery through deployment and operation.
Experience collaborating with cross-functional partners and subject-matter experts.
Location: This role is based in San Francisco, California.
Visa sponsorship: We sponsor visas. 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.

Nice-to-haves

We encourage you to apply even if you meet only some of these:
A track record of building frameworks, SDKs, or developer tools with thoughtful abstractions and a strong user experience.
Experience with distributed job execution, workflow orchestration, sandboxed environments, or large-scale data processing.
Experience building polished, intuitive interfaces for inspecting complex data, comparing experiments, or debugging model behavior.
Familiarity with large language or multimodal model evaluation, including model-based grading, human evaluation, or synthetic data.
Experience working closely with researchers to understand their workflows and turn rapidly evolving needs into durable systems.
Experience at a startup or on a small team, building technically complex products end to end.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipythonmachine learningmlrustreacttypescript

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Parental Leave