Lead the design and delivery of RL environments built from supplied code and domain data. An end-to-end, ML-leaning builder role, not a pure backend or research-only role.

What you'll do

- Decide which data can become a useful environment and clarify what data a lab needs.
- Work backwards from existing benchmarks, or design suitable evaluations.
- Build rewards, graders and verifiers that score agent runs and resist shortcuts and reward hacking.
- Run agent experiments and measure whether post-training improves performance.
- Ship containerised, reproducible setups in Docker, in a standard format such as Harbor.

Non-negotiable

You have personally built at least one RL workplace. Show a runnable repo or inspectable artifact and explain what you built.

Strong skills

ML and RL fundamentals (including gradient descent and how RL environments work); strong recent Python; Linux, Docker, deployment and sandboxes; verifier design that resists gaming. Training or post-training models is a strong extra signal.

📌 Lead RL Environment Engineer (Mumbai)
🏢 Adzzat
📍 Mumbai