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.

You will be interacting on a daily basis with software engineers, machine learning specialists, and researchers to tackle some of the most challenging problems in AI, robotics, and computer vision. We work on a diverse set of problems ranging from solving optimization problems in 3D geometric computer vision, to minimizing latency on hardware accelerators, to designing novel neural network architectures, to applying and advancing the state-of-the-art of machine learning for Autonomy. 

As a localization engineer on the Perception team, you will be responsible for designing and developing a state-of-the-art localization module that utilizes mass-market, lost-cost vehicle sensors. The localization module is a vital component in a safety-critical Autonomy stack and has to operate at an extremely low failure rate and in a diverse set of locations and scenarios. Additionally, you will be responsible for defining and running virtual and on-vehicle validation experiments, continuing to improve our overall end-to-end localization and Autonomy metrics and visualization tools. For this position, we are looking for a software engineer who not only understands the overall autonomy system regarding how various localization poses are being used by downstream users, but also has the passion to deliver a production system capable of powering millions of vehicles. We recognize the unique capabilities each team member can bring and encourage applicants to reach out even if they do not match all of the characteristics described below. 

Responsibilities

  • Work on a high-velocity team of Perception engineers 
  • Design and build a state-of-the-art localization module that combines deep-learned based approaches with traditional state estimation and sensor fusion
  • Collaborate with deep learning experts developing map matching capabilities
  • Deliver a localization module on a power-efficient, edge-compute platform operating under a real-time, automotive grade operating system
  • Work with other Autonomy teams to clearly define localization requirements, build metrics and deliver a localization solution against target accuracy, smoothness and latency
  • Work closely with the mapping team to define minimum map requirements to satisfy localization needs. Provide tools to help evaluate the map quality continuously over time
  • Build tools and dashboards to provide systems health observability and monitoring of the localization stack performance over time
  • Design, implement, and maintain efficient, reusable, reliable, and functionally safe C++ code
  • Apply rigorous engineering practices during validation and deployment

Experience

  • BS/MS (PhD preferred) in Computer Science, Computer Vision, Machine Learning, Robotics, or other quantitative fields or relevant work experience
  • Skilled C++ practitioner
  • Strong mathematical background; familiar with rigid transformations, quaternions, linear algebra, probabilistic and optimization theory
  • Hands-on experience with Bayesian state estimation, e.g. Kalman filters, particle filters, and optimization-based pose estimation, e.g. SLAM
  • Ability to work in a fast-paced environment and collaborate across teams and disciplines
  • Strong communication skills and ability to communicate concepts clearly and precisely
  • Ability to evaluate multiple approaches and make decisions based on first principles

Nice to Have

  • Hands-on experience building localization and/or mapping systems with low-cost sensor data
  • Experience developing localization solutions on automotive grade hardware
  • Experience with visual inertial odometry
  • Good understanding of IMU intrinsics, computer vision, vehicle signals
  • Able to develop inertial navigation system with low quality GPS, IMU and other sensors

OUR COMMITMENT
・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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