Machine Learning Engineer, End-to-end Autonomy (London)

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

• Support the design and development of ML models or model components for end-to-end autonomous driving: ranging from initial data strategy, design, development, experimentation, evaluation, and deployment;
• Able to navigate ambiguities and address uncertainties arising from complex projects involving multiple teams and legacy codebases;
• Writes high-quality code while being rigorous with Machine Learning experimentation;
• Collaborate closely with stakeholders from multiple teams in different time zones to define interfaces and requirements for an end-to-end stack;

Experience

• MS, or higher degree, in a related field, or equivalent industry experience
• Professional experience with ML frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred)
• Experience with data sampling and data curation pipelines for autonomous driving datasets
• Experience in state-of-the-art architectures for end-to-end autonomous driving
• Experience in ML workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization
• Python and C++ experience
• Experience with infrastructure for large-scale datasets and distributed model training
• Experience working with a modern cloud service (AWS, GCP, Azure etc.)

Nice to Have

• Hands-on experience with autonomous driving systems
• Experience with model deployment with NVIDIA stack (e.g. ONNX graphs, TensorRT, profiling)
• Familiarity with recent breakthroughs in ML (e.g. foundation models, pre-training and efficient fine-tuning, multimodal Transformer architectures)
• Knowledge of autonomous driving, large-scale data curation pipelines

WHAT WE OFFER We are committed to creating a modern work environment that supports our employees and their loved ones. We offer many options of the best programs to allow you to do your most meaningful work and to help you shape the future of mobility. Excellent health, wellness, dental and vision coverage A rewarding pension Flexible vacation policy Family planning and care benefits Our Commitment We are an equal opportunity employer and value diversity. Any information we receive from you will be used only in the hiring and onboarding process. Please see our privacy notice for more details.
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