Build and productionize machine-learning models that analyze ad visuals, audio, and text across languages, improving brand safety, moderation, creative generation, and advertising outcomes at scale.
Senior ML Performance Engineer, Inference Optimisation
๐ Description
- Profile inference across model graphs, compiler and runtime behaviour, kernel execution, and memory movement.
- Implement and validate compiler, runtime, and kernel optimisations, including fusion, scheduling, quantisation-aware performance, and custom kernels.
- Build benchmarks and regression tests across models, devices, and software releases.
- Optimise inference for edge targets including NVIDIA Orin/Thor and Qualcomm platforms.
- Collaborate with model, platform, and deployment teams on performance trade-offs and deployment-aware decisions.
- Contribute to team tooling, documentation, and technical discussions.
๐ ๏ธ Requirements
- Experience improving production or production-adjacent systems under latency, memory, bandwidth, power, thermal, or cost constraints.
- Hands-on experience with at least one relevant stack, such as TensorRT, CUDA, Qualcomm QNN, Triton, or OpenCL.
- Ability to work from high-level model behaviour through kernel- and runtime-level execution.
- Strong software engineering fundamentals in debugging, profiling, testing, and maintainable code.
- Clear communication and effective collaboration across ML, systems, and deployment teams.
- Nice to have: embedded or edge ML deployment and benchmarking experience; NVIDIA or Qualcomm SoC familiarity; Python and C++ proficiency; experience supporting engineers or contributing to technical direction.
โจ Benefits
- Market-benchmarked salaries, reviewed annually.
- Meaningful equity.
- Relocation support and visa sponsorship where applicable.
- Hybrid working and core hours.
- Hands-on work in vehicle workshops and labs.
- Learning and development budgets for training, conferences, and growth.
- Health insurance.
- Dental insurance.
Full job description
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.
Hereโs what this particular role covers.
๐ ๏ธ About our Engineering Teams
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.
๐ง Your day-to-day
This is a hands-on role across ML systems, compilers, runtimes, kernels and embedded deployment. You'll find bottlenecks, implement performance improvements, and work with model developers on performance trade-offs so deployment-aware decisions are made early.
๐งฉ What you'll be working on
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
๐ You should apply if
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
Nice to have:
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
๐ฑ Not ticking every box? Thatโs totally okay! If youโre passionate about autonomy and keen to learn, we encourage you to apply even if you donโt meet every requirement.
More about Wayve:
๐ 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. Wayveโs 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 ๐ป- 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.
๐ 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
Weโll always explain the format and work around your availability.
Whatโs in it for you (Location dependant):
๐ฐ Salaries benchmarked against the market annually
๐ Meaningful equity, sharing in the ownership and long term success of Wayve
โ๏ธ Relocation support and visa sponsorship where applicable
โ
Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
๐ Learning and development budgets with support for training, conferences and growth
๐ฉบ 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, youโll 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, weโd 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.
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