Wayve
Senior ML Performance Engineer, Inference Optimisation

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About the Role
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.
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.
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.
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
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
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
🌱 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
- Deep-dive technical interviews [programming, system design & domain-specific interviews; 3 hours total]
- Final interview: mission & values alignment


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What’s in it for you (Location dependant)
- 💰 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.
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