Mechanize
Junior Software Engineer
11mo ago
300000 USD / yearUSAJuniorpythonreinforcement learning
Junior Software Engineer role designing and refining reinforcement learning tasks for AI coding models.
Responsibilities
- You'll design, build, and refine RL tasks. Each task is a self-contained software engineering challenge with a prompt, an environment, and an automated grader. You own the full lifecycle: coming up with the idea, implementing the grading infrastructure, running frontier models against the task, analyzing where and why they fail, and iterating until the task is rigorous and fair.
- Coming up with good task ideas requires being clever: finding situations where a frontier model will fail in interesting ways, which means seeing gaps that the model itself doesn't see. 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.
Conditions
- Compensation includes a $300,000 base salary, equity, and performance bonuses. Top performers can earn more in bonuses than in base salary.
- Strong performers are recognized and promoted quickly. Benefits include health, dental, vision, and life insurance.
- 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 , the Dwarkesh Podcast and Hard Fork .
- 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
Other
- Mechanize builds reinforcement learning environments that frontier AI labs use to train and evaluate their coding models. Learn more at mechanize.work .
- AI models have gotten good at narrow coding tasks but still fail at the complex, judgment-heavy parts of software engineering. We build the environments that expose those failures and help models improve.
- Strong technical fundamentals combined with an intuition for AI model behavior. You need to anticipate where a model will take shortcuts, distinguish genuine capability gaps from grader issues, and understand how a model will interpret a prompt. Most engineers significantly underestimate what frontier coding agents can already do; candidates who have spent significant time working with them will have a real head start.
- Have just graduated or are about to graduate
- Can code in Python
- Are confident working independently
- Are motivated by problems that require both technical skill and creative cleverness
- No prior ML or AI experience required
- We're happy to hire candidates who are very capable, even if they have no prior professional software experience.
- Want a product engineering role building features for end users
- Prefer a highly collaborative team environment with shared ownership
- Want extensive structured mentorship
- This is independent, high-ownership work. You own your tasks from start to finish, with regular check-ins and feedback.