Hiring: Benjamin RL We’re training the next generation of Vedika models. This role sits directly inside RL and post-training research: designing how the model learns after pretraining, how it improves from interaction, how it handles long-horizon tasks, and how we push capability beyond standard instruction tuning. You’ll work on:

- RL training for next-generation Vedika models • GRPO, PPO, DPO and newer post-training methods • Reward models, process rewards and verifiers • Long-horizon reasoning and agent trajectories • Tool-use and computer-use reinforcement • Self-improvement and synthetic training loops • Multi-turn behaviour and memory training • Failure mining from model trajectories • Evaluation systems for reasoning, autonomy and reliability • Research experiments that can become part of the next model generation Compensation: ₹2.6 LPA fixed ₹3.6 LPA CTC Work mode:



Fully remote You’ll get:
- Mac for development • Claude • Codex • Serious compute and research infrastructure • ₹10L–₹50L+ yearly AI/token spend available across the team and experiments This is not a role for someone whose idea of model work ends at prompting or basic fine-tuning. We want someone who can understand a training run, break it, diagnose it, redesign it and make the next model measurably better.

Solid

PyTorch, RL fundamentals, post-training, distributed training and hands-on experimentation matter far more than credentials.

Role: Benjamin RL Vedika — Next Generation Models Send your work, experiments, papers, repos or anything you trained that genuinely got better.

📌 Benjamin RLHF (Nagpur)
🏢 Vedika API
📍 Nagpur