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Senior Machine Learning Engineer, AI Performance

wayveLondon, United KingdomAI Platform
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Experience
Senior
Posted
2 Oct 2026
Status
Open · checked 7d ago

About this role

Wayve is hiring a Senior Machine Learning Engineer for their AI Performance team in London, United Kingdom, to deliver production-ready model releases for autonomous vehicles. This position suits an experienced practitioner who enjoys bridging the gap between high-level machine learning training and strict on-vehicle runtime constraints.

Role Overview

Wayve seeks a Senior Machine Learning Engineer to join the ML Optimisation team in London. The professional will own the end-to-end delivery of model releases, taking them from training environments to deployment readiness under tight runtime constraints. The work involves deep collaboration with downstream inference and performance specialists to ensure models meet product standards for real-world vehicular deployment.

Key Responsibilities

Own the end-to-end delivery of model releases from initial requirements through training, evaluation, iteration, and deployment readiness.
Train and iterate on PyTorch models using a hypothesis-driven approach and run ablations against clear evaluation criteria.
Debug model performance by identifying regressions, root-causing issues, and proposing fixes.
Collaborate with adjacent machine learning and performance engineering teams to hand off models, define bottlenecks, and align on optimisation priorities.
Communicate with stakeholders regarding delivery timelines, trade-offs, and readiness criteria.
Fit models to tight runtime constraints on vehicles and apply practical optimisation techniques like quantisation, distillation, and low-rank methods.

Requirements

Proven experience improving performance in production systems constrained by latency, memory, bandwidth, power, thermal limits, or cost.
Strong hands-on background in training and iterating on deep learning models using PyTorch beyond high-level tooling.
Proficiency with at least one relevant stack or toolchain such as TensorRT, CUDA, Qualcomm QNN, Triton, or OpenCL.
Comfort moving between high-level model behaviour and low-level kernel or runtime execution.
Familiarity with model optimisation concepts like quantisation or distillation.
Strong engineering fundamentals and collaboration skills.

Nice to Have

Experience with models under tight latency and efficiency constraints on edge, embedded, or real-time devices.
Exposure to machine learning systems spanning from training through to deployment handoff.
Background in embedded or edge deployment, including benchmarking on real devices.

Skills and Tools

PyTorch
TensorRT
CUDA
Qualcomm QNN
Triton
OpenCL

Salary and Benefits

Market-benchmarked annual salaries.
Meaningful equity options.
Relocation support and visa sponsorship where applicable.
Hybrid working arrangements with core hours and access to vehicle workshops and labs.
Learning and development budgets for training and conferences.
Comprehensive health insurance, dental coverage, enhanced family leave, pension or retirement plans, therapy access, and team socials.

About the Company

Wayve builds embodied intelligence designed to safely move real vehicles and power future machine ecosystems. The organization pioneers an end-to-end AI approach enabling vehicles to learn directly from real-world experience, utilizing a mapless and hardware-agnostic platform that integrates with global OEM partners.

How to Apply

Candidates should apply on the official company careers page.

Skills and tech stack

PyTorchTensorRTCUDAQualcomm QNNTritonOpenCLDeep Learning

Questions candidates ask

Where is this job located?

The role is based in London, United Kingdom, with a hybrid working model combining office hubs and remote flexibility.

What core framework is required for this role?

Candidates must have strong hands-on experience training and iterating on deep learning models in PyTorch.

What tools or toolchains are expected?

Proficiency with at least one relevant stack or toolchain such as TensorRT, CUDA, Qualcomm QNN, Triton, or OpenCL is required.

Is visa sponsorship available?

Yes, relocation support and visa sponsorship are provided where applicable.

What is the interview process like?

The process includes a 30-minute recruiter screen, a 30-minute hiring manager meeting, 3 hours of deep-dive technical interviews, and a 45-minute final interview focused on mission and values alignment.

Ready to apply?

The application is on the official wayve careers page.

Apply on company site