Key Responsibilities:

- Develop and implement reinforcement learning (RL), imitation learning, vision-language-action (VLA) models, or behavior cloning policies for physical robots.

- Train, test, and validate policies in high-fidelity simulators and transfer them reliably to physical hardware.

- Architect and maintain robot software stacks using ROS 2, integrating sensor data (LiDAR, RGB-D cameras, IMUs) and edge compute platforms.

- Implement kinematics, dynamics, trajectory optimization, and low-level control systems.

- Collaborate with mechanical, electrical, and computer vision teams to debug, benchmark, and stress-test end-to-end robotic applications in real-world lab or field environments.

- Build and manage scalable synthetic data generation, domain randomization, and teleoperation data collection pipelines for AI training.

Good to have:

- Experience with Vision-Language-Action (VLA)



models or foundation models for robotics.

- Bachelor’s, Master’s, or Ph.D. in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, or a related field.

- Prior 3+ years of hands-on software and hardware engineering experience in robotics or embodied AI.

- Robust proficiency in Python and C++.

- Deep experience with ROS / ROS 2, Git, Docker, and CI/CD pipelines.

- Experience with PyTorch or JAX, and physics-based simulators.

- Solid grasp of forward/inverse kinematics, rigid-body dynamics, state estimation, sensor fusion, and classical/learning-based control.

- Proven track record of running and debugging code on real physical robots (e.g., robotic arms, mobile manipulators, humanoids, or quadrupeds).

📌 Robotics Engineer (Physical AI/ VLA Models) (Bengaluru)
🏢 PeopleGene
📍 Bengaluru