Senior Machine Learning Engineer AI Performance
Wayve is a London-headquartered embodied-AI company developing and licensing mapless, vehicle-agnostic driving software for assisted, automated, and robotaxi applications.
About Wayve
Wayve Technologies Ltd. develops the Wayve AI Driver, an end-to-end, data-trained software platform that runs on onboard vehicle compute and native sensors. It is designed for OEM integration across L1 driver assistance through L4 automated driving, without HD maps.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will deliver models from requirements through training, evaluation, iteration, and deployment readiness. You will train PyTorch models, investigate performance regressions, apply model-optimization methods, work across model and runtime layers, and align release priorities with ML and performance engineering partners.
Requirements
- Experience improving performance in production systems with tight constraints
- Hands-on experience training and iterating deep-learning models in PyTorch
- Proficiency with TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL, or a relevant toolchain
- Ability to work from model behavior to kernel and runtime execution
- Knowledge of quantization or distillation
- Strong engineering and collaboration skills
- Experience with constrained edge, embedded, or real-time ML deployment is desirable
- Experience with training, evaluation, deployment handoff, and device benchmarking is desirable
Responsibilities
- Own end-to-end model release delivery
- Train and iterate on PyTorch models
- Evaluate experiments using hypothesis-driven iteration, ablations, and clear criteria
- Debug model-performance regressions and propose fixes
- Apply quantization and distillation where beneficial
- Collaborate with ML and performance engineering teams on model handoffs and bottlenecks
- Communicate delivery timelines, trade-offs, and readiness criteria
