ML Engineer - Robotics

About the Role This role sits at the intersection of machine learning, control systems, and real-world robotics, building the perception, planning, and decision-making pipelines that make autonomous systems truly adaptive. You'll collaborate with frontier AI researchers and hardware engineers to solve hard, interdisciplinary problems that bridge data-driven learning with physical-world constraints — work that directly shapes the next generation of embodied intelligence. What You'll Do 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 workflows. Collaborate with robotics and hardware engineers to deploy models in live environments. Continuously evaluate model performance and robustness across diverse real-world scenarios. What We're Looking For 3–8 years of professional experience in Machine Learning, Robotics, or Computer Vision. Proficiency in Python and C++ for robotics and ML development. Hands-on experience with PyTorch and/or TensorFlow for model development. Proficiency with ROS or ROS2 and integrating ML models into robotics software stacks. Experience with simulation and benchmarking environments such as Gazebo, Isaac Sim, CARLA, MuJoCo, or PyBullet. Solid background in perception, motion planning, and control pipeline design for autonomous systems. Experience with sensor fusion across camera, LiDAR, and IMU data sources. Familiarity with reinforcement learning, imitation learning, or adaptive control techniques. Ability to deploy ML models in real-time or embedded environments. Must be eligible to work in the United States without employer sponsorship. Compensation & Benefits Base salary range: $220,000 – $300,000 USD annually. Visa sponsorship is not available for this role. Location On-site in Mountain View, CA, United States. Local candidates or those willing to relocate are required; remote work is not available for this position.