Field Mechanic Intern

What you'll do

• Architect, implement, optimize, and maintain real-time 3D LiDAR and point-cloud perception, filtering, calibration, and sensor-noise handling algorithms using Modern C++ and Python.
• Own perception functionality end to end, from sensor characterization and technical design reviews through testing, validation, and fleet deployment.
• Develop intelligent agents and automated pipelines for data labeling, dataset curation, edge-case triage, and large-scale offline regression validation.
• Research and build approaches for autonomous recovery, robot learning, adaptive decision-making, and behavior generation across perception-driven robotic applications.
• Partner closely with Controls, System Software, and System Test teams to integrate perception and autonomy decisions into core vehicle software.
• Drive high engineering standards through architectural leadership, comprehensive unit and regression testing, code reviews, technical documentation, and mentoring.
• Expand perception capabilities across multiple robot platforms and operating conditions, including environments where sensor noise and physical conditions introduce new perception challenges.

What you'll need

• Minimum of 8 years of related experience or equivalent work experience.
• Bachelor's, Master's, or Ph.D. in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or a related technical field.
• Strong software engineering proficiency in Modern C++ and Python, including experience with Linux, real-time or low-latency systems, and multithreaded programming.
• Hands-on experience developing perception or autonomy software for physical robotic systems or autonomous vehicles, with strong knowledge of 3D point clouds, filtering, clustering, spatial calibration, and coordinate geometry.
• Experience integrating, debugging, validating, and deploying production perception systems using ROS/ROS2 or comparable robotics middleware, with familiarity with PCL, OpenCV, Docker, and edge-compute environments.
• Experience building automated data or machine learning pipelines, intelligent agents, robot learning systems, automated labeling workflows, or related autonomy capabilities.
• Strong technical communication and architectural leadership skills, including the ability to independently drive design reviews, document technical decisions, collaborate across engineering disciplines, and mentor other engineers.

Our Environment

• Up to 5%-10% of travel may be required. Employees must have a valid driver's license and the ability to drive and/or fly to client locations and company HQ.
• Employees may be required to use a personal credit card for business travel expenses, which are reimbursed based on the program guidelines. Eligible employees may receive a corporate credit card based on role and travel requirements, but a personal credit card may be needed during onboarding until the corporate card is issued.

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