Mechanize

Mechanize

Senior Software Engineer

San Francisco · Senior

Sponsorship not specifiedDetected 133 days ago
PythonDistributed SystemsMachine LearningMentoring

About the role

  • Learn more at mechanize.work http://mechanize.work.
  • Why the work matters AI models have gotten good at narrow coding tasks but still fail at the complex, judgment-heavy parts of software engineering.
  • You will also contribute to shared infrastructure and tooling, and may take on mentorship responsibilities for newer team members.

Responsibilities

  • You'll design, build, and refine RL tasks, owning the full lifecycle from ideation through grading, failure analysis, and iteration.
  • Want a product engineering role building features for end users
  • This is independent, high-ownership work. You own your tasks from start to finish, with regular feedback.
  • You own your tasks from start to finish, with regular feedback.

Requirements

  • Have deep expertise in at least one area of software engineering
  • No prior ML or AI experience required
  • Deep software engineering experience across multiple domains, combined with a strong intuition for AI model behavior.

Compensation

  • Compensation includes a $400,000 base salary, equity, and performance bonuses. Top performers can earn more in bonuses than in base salary.
  • About Mechanize. ~20 person team in San Francisco.
  • Backed by Patrick Collison, Nat Friedman, Daniel Gross, Jeff Dean, Dwarkesh Patel, and Sholto Douglas.
  • Featured in the New York Times https://www.nytimes.com/2025/06/11/technology/ai-mechanize-jobs.html, the Dwarkesh Podcast https://www.dwarkesh.com/p/ege-tamay and Hard Fork https://www.youtube.com/watch?v=M5Lycj5IRwQ.
  • Learn more about the interview process: https://www.mechanize.work/how-our-interview-process-works
  • Learn more about the work: https://www.mechanize.work/what-working-here-is-like

Benefits

  • include health, dental, vision, and life insurance.

Company info

  • At this level, we expect you to work on our most complex tasks: environments involving multi-step workflows, realistic stakeholder interactions, large codebases with real conventions and technical debt, or challenging system design problems.
  • You will use coding agents heavily, and a large part of the job is directing them well, evaluating their output, and knowing when they are failing in subtle ways.

This listing is sourced directly from Mechanize's careers page and normalized into a canonical job model.