Location: Noida or Bengaluru

About the Role

This is the most technically differentiated research role in the company. You'll design the reward functions and RL algorithms that power the post-training behind the models we build — work that genuinely determines whether the models we ship are valuable.

What You'll Do

- Design reward functions and RL recipes, including PPO/GRPO/DPO-family algorithms, for both our platform and our own model post-training
- Ensure customer-supplied reward functions integrate cleanly and train stably on our platform
- Diagnose and resolve RL training instability
- Collaborate closely with our infrastructure team on rollout and environment requirements
- Track new RL research and make the call on what's actually worth adopting

What You'll Bring

- 8+ years of relevant experience, including PhD training, in Machine Learning,



Reinforcement Learning, or a closely related field — the underlying theory here takes years to build, and this is largely a PhD-level hiring bar
- Deep, hands-on experience with modern RL algorithms (PPO, GRPO, DPO, or similar) and reward modeling
- Proficiency in PyTorch or JAX
- Strong statistical intuition for diagnosing why an RL training run is or isn't working

Education

- PhD in Machine Learning, Reinforcement Learning, Computer Science, Statistics, Mathematics, or Physics, from a Tier-1 institution.

Nice to Have

- A research background from a leading RL lab or applied AI company
- Publication record in reinforcement learning or RLHF

📌 Research Scientist (RLHF/RL) (Bengaluru)
🏢 HCLTech
📍 Bengaluru