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
Our data platform team is working on accelerating autonomous driving by providing access to petabytes of data collected by our fleet of autonomous and non-autonomous vehicles. Efficient, fast and cost-effective access to data at large scale is key to tackle the hardest problems in AD/ADAS, from developing the Machine Learning (ML) models for perception and prediction of human driving patterns, to increasing the sophistication of our validation and simulation by identifying rare and interesting real-world driving situations. The data ecosystem developed by the London team is a key building block for developing and testing modern AD/ADAS products that will impact millions of customers.
Our ML and Data pipelines are built on-top of the open-source Flyte orchestration framework and are deployed to AWS. Pipeline code is written in Python. We use SQS and Kafka to automate data connections and leverage BigQuery and Elasticsearch for data storage. We believe strongly in automation and testing to ensure delivery of robust and correct systems. We are a distributed team, working in the UK and US.
Who are we looking for?
The AD/ADAS Data Platform team is looking for a Staff SWE who is passionate about enabling the next generation of automotive software development. Modern ML-based AD/ADAS development requires automatic categorisation and indexing of data based on weather and road conditions, rarity and complexity of driving behaviors and a variety of other factors: for this we are building a data search platform that combines traditional indexing approaches with cutting-edge generative AI technology, which needs to handle large amounts of driving data. The right candidate will have previous experience in building scalable and reliable cloud infrastructure, a user-first attitude, and excellent communication skills to work in a global team. Previous experience in building ML applications is a definite bonus.