Woven Planet is building the safest mobility in the world. A subsidiary of Toyota, Woven Planet innovates and invests in new technologies, software, and business models that transform how we live, work and move. With a focus on automated driving, smart cities, robotics and more, we build on Toyota's legacy of trust and safety to deliver mobility solutions for all. 

For nearly a century, Toyota has been delivering products and services that improve lives. Automation that originated to increase the efficiency of daily activities has evolved into the safe, reliable, connected automobiles we enjoy and depend on today. Now, we are looking to the next 100 years and to extending that dream for a better life for all people. At Woven Planet we strive to build a safer, happier, more sustainable world.

Our unique global culture weaves modern Silicon Valley innovation and time-tested Japanese quality craftsmanship. The complementary strengths enable us to optimize safety, advance clean energy, elevate well-being, and improve how people live, work, and play. We envision a human-centered future where world-class technology solutions expand global access to mobility, amplify the capabilities of drivers, and empower humanity to thrive.

About the Organization

Woven Planet is developing automated driving technology using a data-driven approach. We’re building products at autonomy levels 2-4 to drive both near- and long-term improvements to mobility for all. Woven Planet has the backing of one of the world’s largest automakers, the talent to deliver on our goal, and a built in path to product and revenue—a combination rarely seen in the mobility industry. We’re looking for doers and creative problem solvers with a passion for improving lives.

Each member of our diverse and talented group of software and hardware engineers has the opportunity to make a meaningful impact on our technology and products. Our growing team works in brand new garages and labs in Palo Alto, tests AVs at our dedicated test track in Silicon Valley, and explores the industry’s most compelling research problems at our office in London. With support from our Woven Planet colleagues in Tokyo, our work to improve the future of mobility spans the globe.

In London, our team is accelerating autonomous driving by exploring novel CV/ML solutions utilising one of the largest datasets in the industry: petabytes of data collected from our fourth generation autonomous vehicle platform driving in the Bay Area and an active data collection program in San Francisco using our fleet of second generation capture devices. This dataset enables us to tackle some of the hardest problems in self-driving with ML: from building accurate and up-to-date 3D maps, to understanding human driving patterns, to increasing the sophistication of our simulation tests by having access to rare real-world driving situations. By leveraging this data, Level 5 is uniquely positioned to develop safe, efficient, and intuitive self-driving systems.

We’re working together with the wider research community on these problems by publishing the largest Perception and Prediction open datasets in the industry. Our open source L5kit software enables engineers and researchers to experiment with data-driven approaches to planning and simulation problems using real world driving data and contribute to state-of-the-art solutions.


  • The ability to independently implement research in production using either Python or C++ 
  • Experience with a deep learning framework (TensorFlow, PyTorch, …)
  • Msc/Phd with a proven track record of 1st author publications at top tier conferences
  • Interest in developing algorithms and research ideas and driving them to deployment

Other Beneficial Qualities (Not Required)

  • Background in any of the following:
    • Computer vision
    • NLP
    • Deep learning
    • Robotics
    • Optimal control & reinforcement learning
    • Imitation learning
    • Uncertainty estimation

・We are an equal opportunity employer and value diversity.
・We pledge that any information we receive from candidates will be used ONLY for the purpose of hiring assessment.

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