Software Engineer, Evaluation Platform / Infra

Job summary

Responsibilities

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.

• 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.

What they're looking for

• 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.

Tech stack

• Python
• Rust
• React
• TypeScript