ML Performance Engineer, Inference Optimisation

Wayve; Greater London; Hybrid; GBP 80,000 - 120,000; Full time

Benefits offered by this job

Equity

Relocation support

Hybrid working

L&D budget

Health insurance

Dental

Maternity / Paternity leave

Pension

Job summary

Wayve is building the leading AI platform for autonomous driving with a hybrid work model across London and international offices. The ML performance role focuses on making large transformer models run efficiently on edge devices, balancing latency, memory and power constraints while collaborating with model, platform and deployment teams.

You will optimise inference for edge accelerators like NVIDIA Orin/Thor and Qualcomm platforms, implement kernel-level improvements, and contribute to tooling

Qualifications

• Experience improving performance in production or production-adjacent systems with latency, memory, bandwidth, power, thermal or cost constraints.
• Strong hands-on experience with at least one stack such as TensorRT, CUDA, Qualcomm QNN, Triton or OpenCL.
• Comfortable working from high-level model behaviour down to kernel/runtime-level execution.
• Strong software engineering fundamentals including debugging, profiling, testing and maintainable code.

Responsibilities

• Profiling inference performance across model graphs, compiler/runtime behaviour, kernel execution and memory movement.
• Implementing and validating optimisations in compilers, runtimes and/or kernels, including fusion, scheduling, quantisation-aware performance and custom kernels.
• Building benchmarking and regression tests to track performance across models, devices and software releases.
• Optimising for edge targets such as NVIDIA Orin/Thor and Qualcomm platforms.
• Contributing to team tooling, documentation and technical discussions around ML performance.

Skills

Performance optimization

Python

C++

Cross-team collaboration

Embedded/edge deployment

Tools

TensorRT

CUDA

Qualcomm QNN

Triton

OpenCL

Job description

Описание

Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. Our ML performance team optimises inference for edge accelerators and GPUs, so large transformer-based models run efficiently on low-cost, low-power in-vehicle compute. We work closely with model, platform and deployment teams to turn research models into reliable production systems for Wayve's driving product.

Задачи

• Profiling inference performance across model graphs, compiler/runtime behaviour, kernel execution and memory movement
• Implementing and validating optimisations in compilers, runtimes and/or kernels, including fusion, scheduling, quantisation-aware performance and custom kernels
• Building benchmarking and regression tests to track performance across models, devices and software releases
• Optimising for edge targets such as NVIDIA Orin/Thor and Qualcomm platforms
• Contributing to team tooling, documentation and technical discussions around ML performance

Требования

• You have experience improving performance in production or production-adjacent systems with latency, memory, bandwidth, power, thermal or cost constraints
• You have strong hands-on experience with at least one relevant stack, such as TensorRT, CUDA, Qualcomm QNN, Triton or OpenCL
• You are comfortable working from high-level model behaviour down to kernel/runtime-level execution
• You have strong software engineering fundamentals, including debugging, profiling, testing and maintainable code
• You communicate clearly and work well across ML, systems and deployment teams
• Experience deploying or benchmarking ML models on embedded or edge devices
• Familiarity with NVIDIA and/or Qualcomm SoCs and performance tooling
• Python and C++ proficiency
• Experience supporting other engineers or contributing to technical direction within a small team

Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.

More about Wayve

Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines. Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility.

How we work - Locations & Flexible Working

Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.

The Interview Process

Our process is clear and respectful of your time: Initial call / recruiter screen HM meeting [30 mins] Deep-dive technical interviews [kernel optimisation, system design & domain-specific interviews; 3 hours total] Final interview: mission & values alignment We’ll always explain the format and work around your availability.

Условия

• Salaries benchmarked against the market annually
• Meaningful equity, sharing in the ownership and long term success of Wayve
• Relocation support and visa sponsorship where applicable
• Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
• Learning and development budgets with support for training, conferences and growth
• Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more

A quick, honest note before you apply. Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one. If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you.

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

For more information visit Careers at Wayve. To learn more about what drives us, visit Values at Wayve.

DISCLAIMER

We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.