Senior Robot AI Engineer - ML And Data: General Motors (GM)

The Robotics Software team at GM is developing the next generation of autonomous robotic systems, focusing on autonomous mobile robots (AMRs) and intelligent robotic platforms for complex indoor environments. They are seeking a Senior Robot AI Engineer to help develop and integrate AI systems for these robots. The role involves working on machine learning solutions for perception, sensor fusion, and decision-making, with a focus on bringing innovative and real-world autonomous solutions to the future of work. This is a hands-on problem-solving role within a full development lifecycle, from prototyping to real-world deployment.

Key Responsibilities
Develop AI components for perception, tracking, classification, and decision-making in robotic systems.

Implement and maintain data pipelines for robotic systems, including data collection from edge devices, ingestion, transformation, and cloud storage.

Support the development of offline pipelines for data collection, annotation, training, and evaluation.

Collaborate with multiple teams, including planning, localization, hardware, and system integration, to ensure end-to-end system performance.

Test and validate AI systems in both simulation and real-world environments.

Stay current with relevant tools, frameworks, and techniques in robotics AI.

Required Skills & Qualifications
Education: A Bachelor's, Master's, or Ph.D. degree in Robotics, Computer Science, Electrical Engineering, or a related field.

Experience: Hands-on industry experience in robotics, AI, or perception system development.

Technical Skills:

Strong programming skills in Python and C++.

Familiarity with ML frameworks such as PyTorch or TensorFlow.

Knowledge: A solid understanding of the robot autonomy stack, which includes perception, sensor fusion, localization, mapping, and planning.

Preferred Qualifications
Familiarity with ROS/ROS2, Navigation2, and real-time systems.

Experience with simulation environments and large-scale validation pipelines.

Knowledge of CI/CD practices, Agile development, and scalable ML infrastructure.

Domain experience in AV (Autonomous Vehicles), ADAS (Advanced Driver-Assistance Systems), AMRs (Autonomous Mobile Robots), or industrial automation.