Machine Learning Engineer – Robotics

Role Overview

We are a cutting-edge AI data and model training company collaborating with leading AI labs and enterprises globally. Our team specializes in embodied intelligence, and we seek a skilled Machine Learning Engineer in Robotics to conceptualize, train, and implement intelligent models that drive autonomous systems.

This position intersects machine learning, control systems, and tangible robotics, involving the creation of perception, planning, and decision-making pipelines that enable machines to be adaptive. It is suited for those passionate about solving complex interdisciplinary challenges and integrating data-driven learning with physical system constraints.

This is a full-time role located on-site in Mountain View, CA within the Bay Area. Candidates must have authorization to work in the United States without employer visa sponsorship.

Primary Responsibilities

• Design, develop, and enhance machine learning models focused on perception, motion planning, and control aspects.
• Construct computer vision and sensor fusion frameworks utilizing data from various sensors including cameras, LiDAR, and IMUs.
• Integrate learning-oriented models into robotics software platforms like ROS and ROS2.
• Develop pipelines for collecting data, simulation, and reinforcement-based learning methodologies.
• Partner with robotics and hardware engineering teams for deploying models in operational environments.
• Regularly assess models for performance and robustness across various real-world conditions.

Qualifications and Experience Required

• Bachelor's degree in Computer Science, Electrical or Mechanical Engineering, Robotics, or an equivalent practical background.
• Between 3 to 8 years of hands-on experience in machine learning, robotics, or computer vision, including real-world production application.
• Proficient programming skills in Python and C++ tailored to robotics software development.
• Experience working with ROS/ROS2 frameworks essential for software integration in robotics.
• Strong capabilities in sensor fusion and multi-sensor perception encompassing camera, LiDAR, and IMU.
• Practical exposure to robotics simulation environments such as Gazebo, Isaac Sim, CARLA, MuJoCo, or PyBullet.
• Demonstrated competence in designing, training, and deploying data-driven models within active robotics systems and production pipelines.
• Excellent collaboration and communication skills to work alongside hardware engineers and interdisciplinary teams.
• Must have lawful work authorization in the U.S. without need for visa sponsorship.

Preferred Additional Skills

• Experience with reinforcement learning, imitation learning, or adaptive control approaches.
• Knowledge of PyTorch and/or TensorFlow deep learning frameworks.
• Expertise in deploying machine learning models in real-time or embedded platforms.
• Background in localization, SLAM techniques, or control systems is advantageous.

Compensation and Benefits

• Annual salary range from $220,000 to $300,000, dependent on experience level.
• Attractive equity options and comprehensive benefits package included.

Work Location and Terms

• Position is strictly on-site in Mountain View / Bay Area, California.
• No remote work accommodations available for this role.
• Company does not provide visa sponsorship for employment eligibility.