Senior Machine Learning Engineer

Salary: £60,000 - 60,000 per year

Requirements:

• Proven experience improving performance in production systems with tight constraints such as latency, memory, bandwidth, power, thermal, or cost.
• Strong hands-on experience training and iterating on deep learning models in PyTorch.
• Strong proficiency with at least one relevant stack or toolchain such as TensorRT, CUDA, Qualcomm QNN, Triton, or OpenCL, and confidence learning adjacent frameworks quickly.
• Comfort operating at multiple levels of abstraction, from high-level model behaviour down to low-level kernel and runtime execution.
• Familiarity with model optimisation concepts such as quantisation and/or distillation.
• Ability to reason across multiple levels of abstraction, from model behaviour to runtime and latency implications.
• Strong engineering fundamentals and collaboration skills.
• Experience working on models that must meet tight latency or efficiency constraints in edge, embedded, real-time, or similarly constrained production settings.
• Exposure to ML systems spanning training, evaluation, and deployment handoff.
• Exposure to embedded or edge deployment of ML models, including benchmarking on real devices and handling system-level constraints.

Responsibilities:

• Own end-to-end delivery of model releases, from initial requirements through training, evaluation, iteration, and final readiness for deployment.
• Train and iterate on PyTorch models with a strong experimental approach, including hypothesis-driven iteration, ablations, and clear evaluation criteria.
• Debug and improve model performance using strong analytical skills by identifying regressions, root-causing issues, and proposing fixes.
• Apply optimisation techniques such as quantisation and distillation where beneficial, understanding trade-offs and when methods are appropriate.
• Collaborate cross-functionally with adjacent ML and performance engineering teams to hand off models, define bottlenecks, and align on optimisation priorities.
• Communicate clearly with stakeholders to align on delivery timelines, trade-offs, and readiness criteria.

Technologies:

• AI
• CUDA
• Embedded
• Hardware
• Support
• Machine Learning
• PyTorch

More:

We are Wayve, founded in 2017 and the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate complex environments, improving the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward, and our intelligent, mapless, hardware-agnostic AI products are designed for automakers to accelerate the transition from assisted to automated driving. We work in a fast-paced environment where big problems inspire us, and we embrace uncertainty to unlock groundbreaking solutions. We value diversity, new perspectives, and an inclusive culture where we support one another to deliver impact. We are hiring a Senior Machine Learning Engineer for a high-ownership, delivery-focused team responsible for production-ready model releases as our OEM engagements and release cadence accelerate. We are committed to an inclusive interview experience and encourage candidates to apply even if they do not meet every requirement.

last updated 35 week of 2026