What are the responsibilities and job description for the Physical AI Senior Engineer position at Toyota North America?
What you’ll be doing
- Integrate and deploy AI-enabled robotic solutions to improve manufacturing capability, flexibility, and performance
- Develop and implement computer vision, machine learning, and sensor fusion solutions for real-world manufacturing applications (e.g., bin picking, part handling, inspection)
- Build and optimize AI models for robust performance on industrial hardware, balancing latency, reliability, and compute constraints
- Bridge the gap between modern AI Python scripts and standard industrial automation
- Utilize simulation tools (e.g., Isaac Sim, MuJoCo, or equivalent) to support concept validation, synthetic data generation, and Sim2Real deployment
- Lead and support equipment trials, debugging, and performance validation from proof-of-concept through production deployment (yokoten)
- Collaborate cross-functionally with robotics engineers, controls engineers, and plant manufacturing teams to integrate AI into production systems
- Identify, evaluate, and implement emerging Physical AI technologies through benchmarking, supplier engagement, and industry events
- Ensure solutions meet safety, reliability, and manufacturability requirements, including alignment with applicable standards and internal risk assessments
- Present technical concepts, results, and recommendations to stakeholders, management, and executive leadership
- Manage contractors to design and construct testing cells
- Produce clear, detailed documentation to support future scaling and customer enablement.
What you bring
- Bachelor’s or Master’s degree in Robotics, Computer Science, Data Science, Electrical Engineering, Mechanical Engineering, or related technical field (or equivalent experience)
- 5 years of experience in robotics, AI/ML, or advanced automation development
- Having a full-stack mindset while working in team environments building complete solutions, not just independent AI algorithms, demonstrations, and experiments
- Strong hands-on experience in at least two of the following:
- Computer vision (e.g., detection, segmentation, 3D perception)
- Machine learning / deep learning
- Robotics
- Proficiency in Python, C , ROS-based systems; strong software engineering fundamentals
- Deep understanding of different sensor types (RGBD cameras, LiDAR, Time-of-Flight sensors, etc.) and the ability to tune for image quality accuracy and performance.
What you may bring
- Experience with simulation environments (e.g., Isaac Sim, MuJoCo, Gazebo, or similar)
- Experience with reinforcement learning, imitation learning, or advanced robotics AI techniques
- Experience with Vision-Language-Action (VLA) models and their applications in industrial robotics
- Experience with data collection strategies, including synthetic data or teleoperation-assisted learning
- Exposure to industrial robot programming, PLC integration, or manufacturing systems
- Experience working in a high-volume manufacturing environment, preferably automotive
- Familiarity with relevant robot safety standards (ANSI/RIA, ISO)