Junior AI RL Environment Engineer — SF

Simplify; San Francisco (CA); On-site; USD 255,000 - 345,000; Full time

Job summary

Simplify in San Francisco is hiring a junior software engineer to design and build reinforcement-learning environments for software engineering tasks. You will own the full lifecycle from concept to evaluation against frontier models, using Python and Docker/Linux tools in real engineering-like settings.

You will work on end-to-end problems in a small, fast-moving team, applying strong fundamentals to AI model behavior, and you will be in-person in SF, with opportunities to shape how frontier AI

Qualifications

• Experience with the latest AI tools and models.
• Strong problem-solving ability with intuition for AI model behavior.
• Able to work independently.
• In person in San Francisco.

Responsibilities

• Design and build reinforcement‑learning tasks and environments for software‑engineering challenges.
• Own the full lifecycle: from task concept through evaluation against frontier models.
• Evaluate coding‑agent outputs and identify subtle failure patterns.
• Build Python‑based systems, harnesses, and tooling around model training and evals.
• Work with Docker/Linux environments that mirror real engineering work.
• Own problems end‑to‑end in a small, fast‑moving team.

Skills

AI tools experience

Independent work

Strong problem-solving

Tools

Python

Docker

Linux

Job description

Simplify in San Francisco is hiring a junior software engineer to design and build reinforcement-learning environments for software engineering tasks. You will own the full lifecycle from concept to evaluation against frontier models, using Python and Docker/Linux tools in real engineering-like settings.

You will work on end-to-end problems in a small, fast-moving team, applying strong fundamentals to AI model behavior, and you will be in-person in SF, with opportunities to shape how frontier AI