Senior Machine Learning Engineer, AI Performance at Wayve
United Kingdom
Posted
on-site · full_time · Visa sponsorship
Responsibilities:
- Own end-to-end delivery of model releases: requirements, training, evaluation, iteration and deployment readiness.
- Train and iterate on PyTorch models with hypothesis-driven ablations and clear evaluation criteria.
- Diagnose and fix model performance regressions; profile latency, memory and runtime bottlenecks.
- Apply optimisation techniques (quantisation, distillation, low-rank methods) where trade-offs suit product constraints.
- Collaborate with inference, deployment and embedded teams to hand off models and align optimisation priorities.
- Communicate timelines, trade-offs and readiness criteria to stakeholders.
Requirements:
- Proven experience improving model performance in production under tight constraints (latency, memory, power).
- Strong hands-on experience training and iterating deep learning models in PyTorch.
- Proficiency with at least one deployment/acceleration toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL).
- Comfortable working across model behaviour and low-level runtime/kernel considerations.
- Strong engineering fundamentals, debugging skills and experience in embedded/edge or real-time environments is a plus.