Senior Machine Learning Engineer, AI Performance

• Join a high-ownership AI Platform team delivering production-ready model releases as Wayve’s OEM engagements and release cadence accelerate. • Take on an applied, delivery-focused MLE role built for engineers who like shipping real systems and iterating quickly. • Take models from working in training to meeting product constraints, ready for deployment on-vehicle. • Partner closely with downstream inference and performance specialists to get models deployment-ready. • Keep the system within tight runtime constraints as model capability grows, using practical optimisation techniques such as quantisation, distillation, and low-rank methods where appropriate. • Work hybrid from the London office.

• Bring proven experience improving performance in production systems with tight constraints across latency, memory, bandwidth, power and thermal, or cost. • Train and iterate on deep learning models hands-on in PyTorch rather than only using high-level tooling. • Bring strong proficiency with at least one relevant stack or toolchain such as TensorRT, CUDA, Qualcomm QNN, Triton, or OpenCL, and pick up adjacent frameworks quickly. • Operate comfortably at multiple levels of abstraction, from high-level model behaviour down to low-level kernel and runtime execution. • Reason from model behaviour through to practical runtime and latency implications. • Bring familiarity with model optimisation concepts such as quantisation and distillation, with hands-on experience a strong signal rather than a strict requirement. • Bring strong engineering fundamentals and collaboration skills. • Be based in London for this hybrid role.

• Bring experience with models that must meet tight latency and efficiency constraints in edge, embedded, real-time, or similarly constrained production settings. • Bring exposure to ML systems spanning training, evaluation, and deployment handoff, even without writing kernels day to day. • Bring exposure to embedded or edge deployment of ML models, including benchmarking on real devices and handling system-level constraints. • 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.

• Own end-to-end delivery of model releases, from initial requirements through training, evaluation, iteration, and final readiness for deployment. • Train and iterate on PyTorch models with a strong experimental approach, using hypothesis-driven iteration, ablations, and clear evaluation criteria. • Debug and improve model performance by identifying regressions, root-causing issues, and proposing fixes. • Apply optimisation techniques such as quantisation and distillation where beneficial, understanding the trade-offs and when each method fits. • Collaborate with adjacent ML and performance engineering teams to hand off models, define bottlenecks, and align on optimisation priorities. • Communicate clearly with stakeholders to align on delivery timelines, trade-offs, and readiness criteria.

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 model releases end to end rather than a narrow slice of the pipeline. • Ship applied work quickly on a team built around delivery rather than pure research. • Work across the stack, from model behaviour down to kernel and runtime execution. • Work hybrid, combining time in the London office with working from home. • Collaborate directly with inference, performance, and platform engineering 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.