Software Engineering Intern
About the job
- Are graduating in 2026 or 2027
- 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
- Design, build, and refine reinforcement learning tasks, each task being a self-contained software engineering challenge with a prompt, an environment, and an automated grader
- 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
- Strong technical fundamentals combined with an intuition for AI model behavior
About the company
Mechanize builds high-fidelity reinforcement learning (RL) environments used by leading AI labs to train models on real-world work tasks. Their simulated work scenarios mimic complex job functions–such as building features, debugging code, and deploying software–allowing AI systems to learn through performance and reward signals rather than static data. Mechanize doesn't train AI models itself or ship consumer products; instead, it focuses on creating the specialized virtual environments that help advance AI capabilities, with a current emphasis on automating software engineering and a long-term vision of enabling AI to handle valuable work across the economy. Backed by prominent tech investors, the company is actively hiring engineers to build these environments.
Company Size
11-50
Company Stage
Seed
Total Funding
N/A
Headquarters
N/A
Founded
N/A
Get referred to Mechanize
See people who can refer or advise you
Simplify's Take
What believers are saying
- Mechanize’s environments target automation of high-value software engineering and office work.
- Strong investor backing enables rapid scaling and development of advanced training data.
- Their focus on robustness addresses key AI limitations like unreliability and long-context performance.
What critics are saying
- Major AI labs could outpace Mechanize by building superior in-house RL environments.
- Technical barriers in automating complex tasks may delay product-market fit for years.
- Dependence on a few large AI labs exposes Mechanize to customer concentration risk.
What makes Mechanize unique
- Mechanize builds simulated digital offices for training AI agents in real-world tasks.
- Their environments support multi-agent collaboration and realistic software tools missing in standard RL setups.
- Mechanize sells RL environments to top AI labs, not consumer-facing automation products.
Help us improve and share your feedback! Did you find this helpful?
Benefits
- Health Insurance
- 401(k) Retirement Plan
- Flexible Work Hours
- Unlimited Paid Time Off
- Paid Vacation
- Hybrid Work Options
- Stock Options
- Company Equity