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An AI driver that learns to drive, for assisted and self-driving cars.

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About Wayve

The company, in brief.

What they do

Wayve builds the Wayve AI Driver, an end-to-end AI model that learns to drive from real driving data. It does not use hand-coded rules or prebuilt maps. Car makers use it for driver assistance and for self-driving cars. Wayve has a production agreement with Mercedes-Benz, and Uber rides powered by Wayve run in London.

What they value

  • Big problems: the team leans into uncertainty and hard challenges.
  • Aim high and stay humble: excellence, with continued learning.
  • Back each other to deliver impact for customers, partners, and the team.
  • Humanity at the core of who they are and how they build.
  • Applicants who do not meet every requirement but care about autonomy.

Where they hire

Most roles are in Sunnyvale and London. Others are in Tokyo, Leonberg in Germany, Detroit, Yokohama, and Herzliya in Israel. One role can also be done remotely in Germany. Wayve works on a hybrid model, with office and workshop time. Postings offer relocation support and visa sponsorship where applicable. Some roles in Japan ask for Japanese.

Teams and roles

Wayve started in Cambridge in 2017, and its headquarters is in London. It has offices in Sunnyvale, Vancouver, Leonberg, Yokohama, and Herzliya. It says it raised $2.8 billion in total funding. The board has 173 open roles.

  • Product and delivery: engineers fit the AI Driver into car makers' vehicles, with application software, driver assistance features, and customer integration work.
  • Vehicle software: embedded and platform engineers run the software in the car, and site reliability engineers support the test fleet.
  • AV engineering: machine learning engineers work on the driving model, controls, and model releases.
  • Simulation, evaluation, and validation: teams build GAIA, a generative world model, synthetic data, data quality tools, and evaluation tools.
  • AI platform: engineers build the cloud compute, data, and training infrastructure, and make models run fast on car hardware.
  • Fleet operations: technicians, field engineers, and trainers run the test vehicles.
  • Wayve Labs: researchers work on foundation models for robots.

Most US postings give a pay range.

What they look for

Python is the most common language, and about half of the postings name the automotive industry. Vehicle and embedded roles ask for strong C++, Python, and Linux. The embedded software role says that automotive experience is a plus but not required. Machine learning roles ask for large-scale training and data, and research roles ask for publications at venues such as CVPR or NeurIPS. The inference role asks for TensorRT, CUDA, or Qualcomm tools. Some roles ask for functional safety work, such as ISO 26262. The full-stack role asks for Python, TypeScript, React, and heavy use of AI development tools. Fleet technician roles ask for automotive servicing skills, and some fleet roles ask for a valid driving license.

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