About the RoleYou will work at the intersection of machine learning, control systems, and real-world robotics - building perception, planning, and decision-making pipelines that make machines truly adaptive. This role is ideal for someone who thrives on hard, interdisciplinary problems and loves combining data-driven learning with real-world physical constraints.
This is a fully on-site role based in the Bay Area (Mountain View, CA). Visa sponsorship is not available - candidates must be authorized to work in the United States without employer sponsorship.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 real-world scenarios.
What We're Looking ForRequired:- Bachelor's degree in Computer Science, Electrical/Mechanical Engineering, Robotics, or a closely related field (or equivalent practical experience).
- 3-8 years of hands-on experience in machine learning, robotics, or computer vision with practical production exposure.
- Proficiency in Python and C++ for robotics software development.
- Experience with ROS/ROS2 for robotics software integration.
- Strong experience with sensor fusion and multi-sensor perception (camera, LiDAR, IMU).
- Hands-on experience with simulation environments such as Gazebo, Isaac Sim, CARLA, MuJoCo, or PyBullet.
- Proven ability to design, train, and deploy learning-based models within live robotics systems and production pipelines.
- Strong collaboration and communication skills for working with cross-functional teams including hardware engineers.
- Must be authorized to work in the United States without employer visa sponsorship.
Nice to Have:- Familiarity with reinforcement learning, imitation learning, or adaptive control techniques.
- Experience with PyTorch and/or TensorFlow.
- Solid grasp of deploying ML models in real-time or embedded environments.
- Background in localization, SLAM, or control systems.
Compensation & Benefits- Salary: $220,000 - $300,000 per year, depending on experience.
- Competitive equity and benefits package.
Location- On-site in Mountain View / Bay Area, CA.
- No remote option for this role.
- Visa sponsorship is not available.
