Hiring: Benjamin RL /n We're training the next generation of Vedika models. /n 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. /n You'll work on: /n /n
- RL training for next-generation Vedika models
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- GRPO, PPO, DPO and newer post-training methods
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- Reward models, process rewards and verifiers
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- Long-horizon reasoning and agent trajectories
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- Tool-use and computer-use reinforcement
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- Self-improvement and synthetic training loops
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- Multi-turn behaviour and memory training
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- Failure mining from model trajectories
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- Evaluation systems for reasoning, autonomy and reliability
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- Research experiments that can become part of the next model generation
- ₹10L–₹50L+ yearly AI/token spend available across the team and experiments
/n /n This is not a role for someone whose idea of model work ends at prompting or basic fine-tuning. /n We want someone who can understand a training run, break it, diagnose it, redesign it and make the next model measurably better. /n Solid PyTorch, RL fundamentals, post-training, distributed training and hands-on experimentation matter far more than credentials. /n Role: Benjamin RL /n Vedika — Next Generation Models /n Send your work, experiments, papers, repos or anything you trained that genuinely got better.
📌 Benjamin RLHF (Pune)
🏢 Vedika API
📍 Pune
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