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
Reliable 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 Pune
🏢 Vedika API
📍 Pune