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A leading mobility technology firm in London is seeking innovators to develop advanced machine learning solutions for autonomous driving. Responsibilities include designing ML models, collaborating with cross-functional teams, and leading by example in quality code practices. Ideal candidates have a master's degree and professional experience with machine learning frameworks. The company offers excellent health coverage and a flexible vacation policy.
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.
Team
At Woven by Toyota, we are at the forefront of developing advanced Machine Learning solutions for autonomous driving. Our team tackles groundbreaking challenges in designing state-of-the-art neural networks, pioneering innovative end-to-end architectures, and advancing ML techniques in perception, prediction, and motion planning. We're passionate about pushing the boundaries of autonomous systems through deep learning and optimization, particularly in complex 3D geometric computer vision scenarios. We're seeking passionate innovators and creative problem-solvers eager to redefine mobility through cutting-edge AI and robotics, contributing directly to shaping the future of self-driving technology.
Woven by Toyota is developing a joint project between Toyota Research Institute (TRI) and Woven by Toyota to research and develop a fully end-to-end learned automated driving / ADAS stack. This cross-org collaborative project is synergistic with TRI's robotics division's efforts in Diffusion Policy and Large Behavior Models (LBM).
Responsibilities