Our work spans multimodal data, agentic systems, and physical intelligence — and we collaborate closely with frontier AI labs and enterprises.
As an ML Engineer – Robotics, you will design, train, and deploy intelligent models that power autonomous systems at the intersection of machine learning, control systems, and real-world robotics.
You'll build perception, planning, and decision-making pipelines that make machines truly adaptive, solving hard, interdisciplinary problems that combine data-driven learning with real-world physical constraints.
What You'll DoDevelop 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.
Continuously evaluate model performance and robustness across diverse scenarios and deployments.
What We're Looking ForRequired3–8 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 and benchmarking tools such as Gazebo, Isaac Sim, CARLA, MuJoCo, or PyBullet.
Experience designing and deploying perception, motion planning, and control pipelines for autonomous systems.
Experience with sensor fusion using camera, LiDAR, and IMU data.
Experience with data collection pipel.