Job Description & Details
This is a hands-on R&D role focused on building the next generation of intelligent material handling equipment and autonomous forklifts. If you like bridging the gap between theoretical AI/computer vision concepts and heavy industrial machinery, this position at Toyota gives you the hardware playground to make it happen.
What You'll Actually Be Doing
You'll spend your days prototyping and experimenting with perception systems, automation, and operator-assist tech that will eventually end up on real factory floors. Expect to write code, spin up simulations in ROS or Gazebo, and then step away from the keyboard to physically bolt sensors onto hardware, run live tests, and analyze how well your algorithms hold up in the real world.
The Core Tech Stack
You need solid systems programming skills in Python or C/C++ to drive these prototypes, along with a firm grasp of robotics frameworks like ROS, MATLAB, or Gazebo. Because this role touches both the software and the physical machine, having working knowledge of computer vision, sensor integration, and machine learning pipelines is non-negotiable for success here.
Interview Expectations
When they ask you about a time you troubleshot a complex robotic system failure, the hiring manager wants to see your end-to-end debugging process, specifically how you isolate issues between sensor hardware, communication layers like ROS, and algorithmic code. They'll also likely probe your experience with sensor integration, looking for practical insights into calibration challenges and dealing with noisy real-world data.
Application Advice
Your resume needs to heavily emphasize your hands-on prototyping history rather than just theoretical coursework. Make sure keywords like ROS, C++, Python, computer vision, and sensor integration stand out clearly so you easily clear the initial ATS screening before a senior engineer reads your project breakdown.