About this role

Develop and optimize ML models for perception, motion planning, and control.
Build computer vision and sensor-fusion systems using camera, LiDAR, and IMU data.
Integrate learning-based models with robotics software stacks (ROS/ROS2).
Design pipelines for data collection, simulation, and reinforcement learning.
Collaborate with robotics and hardware engineers to deploy models in live environments.
Continuously evaluate model performance and robustness across diverse scenarios.

Proficiency in Python and C++, with hands-on experience using PyTorch and/or TensorFlow to build and deploy models.
Experience with ROS or ROS2 and integrating ML models into robotics software stacks for live deployments.
3–10 years of experience in machine learning, robotics, or computer vision.
Strong grasp of robotics concepts such as localization, SLAM, control systems, and sensor fusion.
Experience with simulation environments (e.g., Gazebo, Isaac Sim, CARLA, MuJoCo, or PyBullet) for training, testing, or validation.
Familiarity with reinforcement learning, imitation learning, or adaptive control techniques applicable to robotics.
Experience deploying ML models in real-time or embedded environments.
Nice to Have: Experience with on-board/edge deployment and optimizing models for constrained hardware.

ML Engineer – Robotics

Key skills