Senior ML Performance Engineer, Inference Optimisation

Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Engineering Teams Our ML performance team optimises inference for edge accelerators and GPUs, so large transformer-based models run efficiently on low-cost, low-power in-vehicle compute. We work closely with model, platform and deployment teams to turn research models into reliable production systems for Wayve's driving product. 🧠 Your day-to-day This is a hands-on role across ML systems, compilers, runtimes, kernels and embedded deployment. You'll find bottlenecks, implement performance improvements, and work with model developers on performance trade-offs so deployment-aware decisions are made early. 🧩 What you'll be working on - Profiling inference performance across model graphs, compiler/runtime behaviour, kernel execution and memory movement - Implementing and validating optimisations in compilers, runtimes and/or kernels, including fusion, scheduling, quantisation-aware performance and custom kernels - Building benchmarking and regression tests to track performance across models, devices and software releases - Optimising for edge targets such as NVIDIA Orin/Thor and Qualcomm platforms - Contributing to team tooling, documentation and…