About the job
Woven by Toyota is driving Toyota’s transformative journey into a modern mobility enterprise. Our vision is to redefine mobility through innovative, human-focused solutions that serve society at large.
Our initiatives revolve around four core areas: Advanced Driver Assistance Systems (ADAS), our autonomous driving technologies; Arene, our software platform for software-defined vehicles; Woven City, a testbed for mobility innovations; and Cloud & AI, the digital backbone supporting our collaborative efforts. Our business-critical functions empower these teams to achieve a singular ambitious objective: creating a world with zero accidents and enhanced well-being for everyone.
TEAM
At Woven by Toyota, we confront challenges in Autonomy at the intersection of AI, Robotics, and Advanced Driving. Our work encompasses analyzing vast amounts of multimodal driving data, tackling optimization challenges, reducing latency on hardware accelerators, deploying scalable machine learning (ML) training and evaluation pipelines, and innovating neural network architectures to advance state-of-the-art ML for Perception, Prediction, and Motion Planning. We are seeking proactive and innovative problem solvers to join our mission of enhancing mobility for all through human-centered automated driving solutions.
WHO ARE WE LOOKING FOR?
We are in search of a seasoned, hands-on ML Engineering Manager to lead a team of skilled and passionate ML Platform engineers. This role will involve close collaboration with our ML teams to enhance and scale our overall ML engineering initiatives, facilitating the deployment of Perception, Prediction, and Planning ML models alongside our AD/ADAS stack into millions of Toyota vehicles.
This position will focus on developing and implementing tools, automation, and infrastructure that support the entire ML software lifecycle, ranging from data loading of curated ML datasets, large-scale ML model training, evaluation, and deployment, including quantization and the conversion of models into formats compatible with our edge devices.
The ideal candidate possesses a collaborative spirit and a deep-seated passion for self-driving technology and its potential global impact. You will leverage your expertise in machine learning, a comprehensive understanding of the model lifecycle, and experience in developing tools and pipelines for vehicle perception, localization, prediction, and planning.
