Software Engineer I ( Research Engineer )

You'll own complex, long-running technical workflows end to end — implementation, validation, documentation, and follow-through — and design and maintain the tasks, benchmarks, and test suites that measure CUA capability as the underlying models, APIs, and infrastructure keep evolving. You hold an exacting bar for code quality: you love writing tests, you're fluent with deployment strategies like canary releases and rollbacks, and you bring a strong sense of risk management.

Job Title: Software Engineer I  ( Research Engineer )
Location - Remote 
Duration - 12 Months

Job Description
Role Summary
We're looking for a software engineer to help build and evaluate CUA (Computer Use Agents) — models trained to operate real software and complete computer-based tasks the way a skilled engineer would. You'll own complex, long-running technical workflows end to end — implementation, validation, documentation, and follow-through — and design and maintain the tasks, benchmarks, and test suites that measure CUA capability as the underlying models, APIs, and infrastructure keep evolving. You hold an exacting bar for code quality: you love writing tests, you're fluent with deployment strategies like canary releases and rollbacks, and you bring a strong sense of risk management. You have a sharp eye for weak implementations and give (and take) blunt, direct feedback. You're also fluent with AI coding assistants like Claude Code, Codex, or Cursor, with your own well-developed best practices for using them, and you're proficient in Rust, Python, and/or TypeScript. Above all, you bring strong debugging and experimental discipline — the ability to investigate discrepancies across code, configuration, infrastructure, and results within the CUA stack, and turn ambiguous findings into reproducible conclusions.

Mandatory Requirements:

Passionate about coding since childhood with a drive to dive deep into technology. You maintain extremely high standards for code quality, love writing tests, and are familiar with deployment strategies like canary releases and rollbacks. You possess a strong sense of risk management.
Familiar with at least one AI coding assistant (e.g., Claude Code, Codex or Cursor) and have developed your own insights and best practices for using them.
Proficient in one or more of the following languages: Rust, Python, or TypeScript.
Possess a sharp eye for spotting "garbage" code/implementation. You are willing to give blunt, direct feedback (call out bad code) and are equally thick-skinned enough to receive it.
Strong debugging and experimental discipline. You can investigate discrepancies across code, configuration, infrastructure, and results, then turn ambiguous findings into reproducible conclusions.
Comfortable owning complex, long-running technical workflows end to end, including implementation, validation, documentation, and follow-through.

Bonus Qualifications:

Experience in server-side or infrastructure development, with a track record of building highly available and stable systems.
Exceptional communication skills. Able to engage effectively with algorithm teams, product managers, operations, and executives. You can translate complex technical concepts into language that absolutely anyone (technical or non-technical) can easily understand.
You have your own carefully maintained open-source project(s)—the number of GitHub stars doesn't matter.
Experience with ML evaluation, distributed systems, developer infrastructure, or large-scale testing.
Experience maintaining benchmarks or test suites while underlying models, APIs, and infrastructure evolve.