ML Engineer - Robotics

ABOUT THE ROLE

This role sits at the intersection of machine learning, control systems, and real-world robotics, powering 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 real-world physical constraints — work that directly shapes the future 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 robotics simulation tools such as Gazebo, Isaac Sim, CARLA, MuJoCo, or PyBullet.

• Solid background in designing and deploying perception, motion planning, and control pipelines for autonomous systems.

• Experience with sensor fusion using camera, LiDAR, and IMU data.

• Familiarity with reinforcement learning, imitation learning, or adaptive control techniques.

• Ability to evaluate and improve model robustness across varied deployment environments.

• Curiosity, grit, and a passion for pushing the boundaries of embodied AI.

COMPENSATION & BENEFITS

Base salary: $220,000–$300,000 USD annually. No visa sponsorship is available for this role; candidates must be eligible to work in the United States without sponsorship.

LOCATION

This is a fully on-site role based in Mountain View, CA. Local candidates or those willing to relocate are encouraged to apply.