ML Engineer – Robotics
Clera
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.
Location
This is an on-site role based in Mountain View, CA. Candidates must be able to work on-site and collaborate closely with cross-functional engineering teams. Visa sponsorship is not available.
Compensation
Base salary range: $220,000 - $300,000 USD annually, commensurate with experience.