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Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. The AI Platform team builds the foundations that enable machine learning engineers and researchers to train, evaluate, and deploy models at scale.
In this Staff-level role on the AI Libraries team, you will create high-quality platforms, tools, and reusable abstractions that support thousands of GPUs and accelerate the development of autonomous-driving technology. You'll work closely with machine learning teams to understand their workflows and translate complex requirements into stable, scalable, and intuitive software.
Your day-to-day responsibilities include designing and writing Python code, leading projects from discovery through delivery, improving engineering standards, and supporting users as they push the scale and performance of their models. You'll build modular libraries for multimodal data loading, distributed training and inference, checkpointing, and observability. You'll improve the reliability, performance, and developer experience of systems used across Wayve, helping teams train models efficiently on large GPU clusters and work with camera, radar, lidar, and other data sources.
You'll remain hands-on while guiding other engineers and driving projects end-to-end, from shaping requirements through adoption and maintenance. You'll set technical direction, raise the bar for software architecture, testing, and observability, and help shape how the organization approaches platform engineering.
Wayve operates a hybrid working model combining in-person collaboration in dedicated office spaces with focused remote work time. Main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver, and Leonberg. The company is not a mature, fully-structured organization—much of how they work is still being written, and you'll help write it.
REQUIREMENTS:
- Deep Python expertise and proven track record of leading the design, delivery, and long-term evolution of high-quality software systems at scale
- Ability to turn complex requirements across ML teams into stable, reusable libraries and clear APIs
- Experience with concurrent, parallel, or distributed computing (important)
- Familiarity with ML frameworks such as PyTorch or TensorFlow (highly valuable)
- Familiarity with cloud environments, ideally Azure (highly valuable)
- Strong software architecture, testing, and observability practices
- Ability to guide other engineers and drive projects end-to-end
Note: The posting encourages applications even if you don't meet every requirement, particularly if passionate about autonomy and keen to learn.
