About the Role
A Series A AI/ML platform company is looking for an ML Engineer – Robotics to design, train, and deploy machine learning models that power autonomous systems. You'll work at the intersection of machine learning, control, and real-world robotics — building perception, planning, and decision-making pipelines alongside hardware and robotics engineers. Your work will help make machines adaptive and robust across diverse, real-world scenarios.
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.
- Collaborate with robotics and hardware engineers to deploy models in live environments.
- Continuously evaluate model performance and robustness across diverse scenarios.
What We're Looking For
Required (Dealbreakers):
- 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.
Required:
- 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.