Staff ML Performance Engineer

Position:
Staff ML Performance Engineer (Compiler)

Company:
Wayve

Location:
United Kingdom, London

Short Summary:
As a Staff ML Performance Engineer, you’ll play a key role in high-impact projects, optimising ML inference for edge accelerators and GPUs, focusing on running large transformer-based models efficiently on low-cost, low-power edge devices.

Responsibilities:
- Identify, implement and validate optimisations in ML compilers, runtimes, and kernels (e.g. operator fusion, scheduling, quantisation-aware performance, custom kernels).
- Profile and pinpoint bottlenecks across the full inference stack and deliver measurable improvements.
- Build robust benchmarking and regression testing to ensure performance improvements hold across models, devices, and software releases.
- Develop and optimise for multiple target platforms (e.g. NVIDIA Orin/Thor, Qualcomm).
- Collaborate with model developers to influence architecture and training/deployment decisions that affect on-device performance.
- Contribute to technical roadmaps and tooling and help raise the standard of performance engineering across the team.

Requirement:
- Proven experience improving performance in production systems with tight constraints (latency, memory, bandwidth, power/thermal, or cost).
- Strong proficiency with at least one relevant stack/toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL, MLIR, ONNX).
- Comfort operating at multiple levels of abstraction — from high-level model behaviour down to low-level kernel/runtime execution.
- Strong software engineering fundamentals (debugging, profiling, testing, and maintainable code).
- Clear communicator and collaborative teammate; able to align multiple stakeholders on performance trade-offs and priorities.

Benefits:
Wayve is committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives.