Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.
Our work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud & AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.
THE TEAM
At Woven by Toyota, we work on a diverse set of problems ranging from solving optimization problems in 3D geometric computer vision to designing and deploying novel ML architectures for perception, prediction, and motion planning for Toyota customers. We are looking for doers and creative problem solvers to join us in improving mobility for everyone with self-driving technology. You will be interacting on a daily basis with other software and hardware engineers and researchers to tackle some of the most challenging problems in AI, robotics, and computer vision.
WHO ARE WE LOOKING FOR?
The AD/ADAS team is seeking a seasoned ML engineer to support the development of foundation models for our autonomy stack. You will be responsible for curating the right multi-modal data, identifying the most suitable model architectures, steering towards the best training paradigms, optimizing the infrastructure for the highest utilization, and ultimately focusing on efficient deployment for onboard and offboard use cases. Fortunately, you will be doing this with a world-class team of exceptional engineers.
We recognize the unique capabilities each team member brings and encourage applicants to reach out even if they do not match all of the characteristics described below.
