Hiring: Benjamin RL

nWe're training the next generation of Vedika models.

nThis 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.

nYou'll work on:

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- 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
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nCompensation:

n₹2.6 LPA fixed

n₹3.6 LPA CTC

nWork mode:



Fully remote

nYou'll get:

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- Mac for development
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- Claude
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- Codex
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- Reliable compute and research infrastructure
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- ₹10L–₹50L+ yearly AI/token spend available across the team and experiments
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nThis is not a role for someone whose idea of model work ends at prompting or basic fine-tuning.

nWe want someone who can understand a training run, break it, diagnose it, redesign it and make the next model measurably better.

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

nRole: Benjamin RL

nVedika — Next Generation Models

nSend your work, experiments, papers, repos or anything you trained that genuinely got better.

📌 Benjamin RLHF (Pune)
🏢 Vedika API
📍 Pune