Software Engineer, AI Libraries

• Join the AI Libraries team building the platforms, libraries, and tools that let Wayve’s ML engineers and researchers train, evaluate, and scale models efficiently. • Build stable, scalable, modular systems that support large-scale ML development in a hands-on engineering role. • Work closely with ML teams across Wayve to understand their needs and design reusable abstractions. • Improve the reliability, performance, and usability of Wayve’s training infrastructure. • Play a key role in maturing the AI platform and getting autonomous driving technology into customers’ hands. • Focus on building reliable software, libraries, infrastructure, and tooling rather than ML modelling itself. • Work hybrid from the London office.

• Bring strong Python programming experience. • Show proven experience designing, building, and maintaining software systems from concept through to delivery. • Bring strong software architecture and system design skills. • Build tools, platforms, or libraries for internal or external users. • Understand testing, observability, maintainability, and engineering best practices deeply. • Work in cloud environments, ideally Azure. • Bring experience with concurrent, parallel, or distributed computing. • Bring familiarity with ML frameworks such as PyTorch, TensorFlow, or PyTorch Lightning. • Work closely with technical stakeholders to refine requirements and deliver practical, scalable solutions. • Care about clean abstractions, scalable architecture, and software other engineers can depend on. • Be based in London for this hybrid role.

• Bring experience working with large GPU clusters or distributed training environments. • Bring familiarity with distributed training techniques such as DDP or FSDP. • Bring experience with observability tools such as Prometheus, Grafana, Datadog, or OpenTelemetry. • Bring experience with data pipeline orchestration tools such as Airflow, Flyte, Ray, Metaflow, or Argo Workflows. • Bring experience with containerisation and infrastructure tooling such as Docker, Kubernetes, or Terraform. • Profile or optimise ML systems using tools such as NVIDIA Nsight. • Understand ML workflows and researcher experience, even without focusing on model development yourself. • Apply even if you do not meet every requirement, as Wayve encourages people passionate about self-driving cars to get in touch. • Let Wayve know if you need any accommodations or adjustments to take part fully in the interview process.

• Design, build, and maintain scalable Python libraries and tools used by ML engineers and researchers across Wayve. • Develop robust abstractions for data loading, distributed training, inference, checkpointing, and model evaluation workflows. • Support training at scale across large GPU clusters and cloud-based infrastructure. • Work closely with ML teams to create tools that are reliable, well-documented, observable, and easy to adopt. • Improve engineering quality across ML systems through strong architecture, testing, monitoring, and maintainability practices. • Optimise data and training pipelines for multi-modal sources including camera, radar, lidar, and other sensor data. • Contribute to the evolution of Wayve’s AI platform as autonomous driving capabilities scale.

Wayve is one of the most exciting AI companies in the UK right now. They are tackling one of the hardest problems in technology, teaching machines to drive, and they are doing it with an approach that the rest of the industry is now converging towards. Backed by SoftBank, Microsoft, NVIDIA, Uber, Mercedes-Benz, Nissan, and Stellantis, Wayve has raised $2.8 billion in total funding and reached a valuation of $8.6 billion. With over 1,000 employees across London, Silicon Valley, Vancouver, Leonberg, Herzliya, and Tokyo, Wayve is scaling fast while keeping its London HQ at the centre. What stands out on Glassdoor (4.4/5 from 112+ reviews) is how consistently employees praise the culture, the calibre of colleagues, and the quality of the technical work. People describe it as some of the most interesting work of their careers. Wayve also offers an on-site chef, private healthcare, competitive pay with equity, and a genuine learning environment where you work alongside world-class ML researchers and engineers. That said, some reviews flag that the pace can be intense and that working across global time zones can stretch working hours. If you are an engineer, researcher, or operator who wants to work on genuinely frontier technology with real-world impact, and you thrive in fast-paced, mission-driven environments, Wayve is a rare opportunity.

• Work on high-impact systems that directly support the development of autonomous driving technology. • Help scale training and evaluation infrastructure across large GPU clusters. • Build software used by ML engineers and researchers working at the frontier of embodied AI. • Join a team focused on strong engineering standards, practical abstractions, and scalable platform design. • Play a meaningful role in bringing autonomous driving technology closer to real-world deployment. • Work hybrid, combining time in the London office with working from home.

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Its advanced AI software and foundation models let vehicles perceive, understand, and navigate any complex environment, improving the usability and safety of automated driving systems. Wayve builds intelligent, mapless, hardware-agnostic AI products for automakers, aiming to accelerate the transition from assisted to automated driving and create autonomy that propels the world forward.