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 good.

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 workplace 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 (Bengaluru)
🏢 HCLTech
📍 Bengaluru