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 environment. Show a runnable repo or inspectable artifact and explain what you built. Robust 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