Senior Machine Learning Engineer, AI Performance

📋 Description Own end-to-end delivery of model releases for OEM engagements and production-ready release cadence. Train and iterate PyTorch models with an experimental, hypothesis-driven approach. Debug and improve model performance, identify regressions and propose fixes. Apply optimisation techniques (quantisation, distillation) and evaluate trade-offs for in-vehicle Collaborate with adjacent ML and performance teams to hand off models and align on priorities. Communicate delivery timelines, trade-offs, and readiness criteria to stakeholders. 🎯 Requirements Proven experience improving performance in production systems with tight constraints (latency Strong hands-on PyTorch experience (not just high-level tooling). Proficiency with stack/tooling (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL) and ability to Comfort operating across abstraction levels from high-level model behavior to low-level runtime Familiarity with model optimisation concepts such as quantisation and/or distillation. Ability to reason about runtime/latency implications across multiple levels of abstraction. 🎁 Benefits Inclusive interview process with accommodations if needed. Transparent, diverse, and respectful culture. Learn more about Wayve's values at Careers page.