Reinforcement Learning Engineer at beebom

About the role

Work on cutting-edge reinforcement learning applications for robotics and autonomous systems. Develop agents that learn complex behaviors through interaction.

Responsibilities

• Design and implement RL algorithms (PPO, SAC, DQN)
• Build simulation environments for agent training
• Optimize reward functions and training procedures
• Deploy trained agents to physical systems

Requirements

• MS/PhD in CS, Robotics, or related field
• Strong understanding of RL theory and algorithms
• Experience with simulation tools (MuJoCo, PyBullet, Isaac Gym)
• Proficiency in Python, PyTorch, JAX
• Knowledge of control theory is a plus

Benefits

• Cutting-edge projects
• Research publication
• Hardware lab access
• Equity