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Sign Up to ReadBefore 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 technical discussions around ML performance
You should apply if
You have experience improving performance in production or production-adjacent systems with latency, memory, bandwidth, power, thermal or cost constraints
You have strong hands-on experience with at least one relevant stack, such as TensorRT, CUDA, Qualcomm QNN, Triton or OpenCL
You are comfortable working from high-level model behaviour down to kernel/runtime-level execution
You have strong software engineering fundamentals, including debugging, profiling, testing and maintainable code
You communicate clearly and work well across ML, systems and deployment teams
Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.
The Interview Process:
Our process is clear and respectful of your time:
Initial call / recruiter screen
Deep-dive technical interviews [programming, system design & domain-specific interviews; 3 hours total]
Final interview : mission & values alignment
We’ll always explain the format and work around your availability.
Part of the week in the office
Relocation offered
Visa sponsored
Wayve
Office in London, United Kingdom
Also hiring in Sunnyvale, United States, Germany, Detroit, United States and 1 more place
1 of their 117 open roles is remote
Worth a look before you spend an evening tailoring a CV for it.
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