Machine Learning Engineer, Performance Tooling

• Join the AI Performance Tooling team within Wayve’s AI Performance organization, making model training and inference faster, more efficient, and more predictable across cloud and embedded hardware. • Enable data-driven AI performance decisions across priority workloads and hardware targets. • Measure performance in ways teams can trust, monitor trends, catch regressions, predict the cost of changes before running them, and advise on bottlenecks and prioritised opportunities. • Build tools that reason across the AI stack, covering models and operators, compilers, runtimes, accelerators, and distributed training infrastructure. • Turn profiling data into a clear picture of where time, memory, power, and compute go. • Show what proposed changes will do to latency, throughput, compute spend, and capacity. • Work closely with model, compiler, runtime, platform, and hardware teams, bringing a cross-stack view that turns measurement into clear recommendations. • Work hybrid from the London office.

• Bring deep, hands-on performance engineering experience in complex systems, covering profiling, roofline analysis, latency and throughput optimisation, and root-causing what limits a workload. • Show a track record of owning a tool or service end to end, through design, delivery, and adoption by other teams. • Bring strong Python skills and comfort profiling and instrumenting large production codebases. • Develop deep learning models hands-on with PyTorch. • Turn noisy measurements into conclusions you can defend using solid data analysis skills. • Turn an ambiguous performance question into a measurable one and prioritise what actually matters. • Communicate quantitatively clearly enough to influence another team’s priorities. • Be based in London for this hybrid role.

• Bring experience with compilers, runtimes, or accelerator hardware alongside model-level work. • Bring experience with distributed training infrastructure at scale. • Optimise workloads for embedded hardware targets as well as cloud. • Build self-service tooling that other engineering teams adopt without hand-holding. • Set up monitoring and regression alerting across model builds and training runs. • Bring previous experience with autonomous systems, robotics, or another safety-critical domain. • Let Wayve know if you need any accommodations or adjustments to take part fully in the interview process.

• Design and build reliable, self-service performance tools that scale across models, hardware targets, and development workflows. • Shape how Wayve measures and predicts AI performance, setting the standards other teams build on. • Model theoretical peak for a platform, compare it with achieved performance, and pinpoint where efficiency is lost at layer and op level. • Predict the latency, memory, utilisation, and compute cost of a model or recipe change before spending compute on it. • Own monitoring and regression alerting across model builds and training runs. • Work with training and runtime engineers to set performance targets and make the case with data.

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.

• Own performance tooling end to end, from design through to adoption by other teams. • Work across the full AI stack rather than a single layer of it. • Set the measurement standards the wider organisation builds on. • Work hybrid, combining time in the London office with working from home. • Collaborate directly with model, compiler, runtime, platform, and hardware teams. • Contribute to an inclusive environment that values diversity and new perspectives.

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.