About the role
Most job posts are designed to collect as many applications as possible.
This is not one of them.
At Simplify, we work directly with startup founders to help them hire for high-priority roles.
We're partnering with a top AI training lab in San Francisco to hire a junior software engineer — and they pay like it's a senior role: $300K base + equity + bonus, for new grads.
About the company
One-liner: Building high-fidelity RL environments used to train frontier AI models on real software-engineering work
Stage: 11–50 people, HQ in SF. They work directly with the top AI labs — their environments are used to train state-of-the-art models.
Today, AI models learn coding from static datasets and toy problems. This team builds the realistic, simulated engineering environments — long-horizon tasks, real tooling, real failure modes — that frontier labs use to train and evaluate the next generation of coding agents.
What you'll work on
- 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
Must-have
- Strong Python skills
- Experience working with the latest AI tools and models
- Exceptional problem-solving ability — strong technical fundamentals and intuition for AI model behavior
- Able to work independently
- In person in San Francisco
- US work authorization
Nice to have
- ML or AI experience (e.g., you've trained your own models) — not required
- Strong math/CS background (competitions like USACO/ICPC/olympiads)
- Competed in quiz bowl, debate, robotics
- Impressive personal projects
Why join
- $300K base + equity + bonus — at the junior level
- Your work directly shapes how frontier AI models learn to do real engineering
- Small fast moving team, no bureaucracy — high ownership from day one
- Work at the frontier of RL, agents, and evaluation with the top AI labs as your customers
