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.