Woven By Toyota · London
Skills: Python, SQL
Woven by Toyota(https://woven.toyota/en) 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
An autonomous driving system typically comprises Sensing, Perception, Localization, Planning, and Control components. The World Understanding team owns responsibilities for Sensing, Perception, and Localization within Woven by Toyota for autonomous driving development. Specifically, the Sensor & Calibration sub-team, operating under the World Understanding team, focuses on Intrinsic and Extrinsic calibration of autonomous driving sensors, including Camera, LiDAR, Radar, and IMU. Our scope of work also encompasses the quality management of sensor data for post-processing activities and the operational management of calibration for our autonomous driving test vehicles.
WHO ARE WE LOOKING FOR?
The Sensor & Calibration sub-team is seeking a Software Engineer to support the development of ground truth sensor calibration & data validation tools that live in the cloud and fuel our next-generation autonomous driving systems.
The selected candidate will be responsible for accelerating our calibration & data validation systems as well as maintaining & improving its infrastructure used across multiple teams. The scope of this role encompasses the following: (1) Developing and scaling val…
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