Machine Learning Engineer, Performance Tooling

Requirements

• Built or owned significant parts of an ML compilation or graph-lowering pipeline.
• Deep experience with quantisation in compilation — precision typing, PTQ integration, debugging accuracy loss from compiler transforms.
• Strong Python; comfortable building and testing compiler infrastructure in production codebases.
• Proficiency with at least one of: MLIR, ONNX, TensorRT, Qualcomm QNN, PyTorch graph capture/export.
• Experience with multi-target compilation or graph partitioning across hardware backends.
• Ability to reason about correctness and performance trade-offs at each compiler stage.

What You'll Be Doing

• Own the ML compilation pipeline end-to-end on NVIDIA (TensorRT) and Qualcomm (QNN) targets.
• Design and implement compiler passes with accuracy and latency gates.
• Extend precision typing and graph-splitting logic for new architectures and SoCs.
• Partner with model and training teams on compilability.
• Build regression and benchmarking to validate changes across releases.
• Set technical direction and mentor on compiler design.

Perks and Benefits

• Wayve is committed to creating an inclusive interview experience.
• Encouragement for applicants passionate about self-driving cars.
• Promotes a diverse, fair, and respectful culture.
• Embraces unique skills and perspectives of individuals.