Wayve
Machine Learning Engineer, Performance Tooling

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About us
Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.
Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.
In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.
At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.
Make Wayve the experience that defines your career!
The role
You’ll join the AI Performance Tooling team within Wayve’s AI Performance organization, which makes model training and inference faster, more efficient, and more predictable across cloud and embedded hardware. Our mission is to enable data-driven AI performance decisions across priority workloads and hardware targets: Measure performance teams can trust; Monitor trends and catch regressions; Predict the cost of changes before we run them; Advise on bottlenecks and prioritized opportunities.
You’ll build tools that reason across the AI stack — models and operators, compilers, runtimes, accelerators, and distributed training infrastructure — turning profiling data into a clear picture of where time, memory, power, and compute go, and what proposed changes will do to latency, throughput, compute spend, and capacity. You’ll work closely with model, compiler, runtime, platform, and hardware teams, bringing a cross-stack view that turns measurement into clear recommendations.
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.
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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.
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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.
Key responsibilities
- Design and build reliable, self-service performance tools that scale across models, hardware targets, and development workflows.
- Shape how Wayve measures and predicts AI performance, and set the standards other teams build on.
- Model theoretical peak for a platform, compare with achieved performance, and pinpoint where efficiency is lost at layer and op level.
- Predict latency, memory, utilization, and compute cost of a model or recipe change before spending compute.
- Own monitoring and regression alerting across model builds and training runs.
- Work with training and runtime engineers to set performance targets and make the case with data.
About you
In order to set you up for success as a Software Engineer, AI Performance Tooling at Wayve, we’re looking for the following skills and experience.
Essential
- Deep, hands-on performance engineering in complex systems: profiling, roofline analysis, latency and throughput optimization, and root-causing what limits a workload.
- A track record of owning a tool or service end to end — design, delivery, and adoption by other teams.
- Strong Python skills, and comfort profiling and instrumenting large production codebases.
- Hands-on experience developing deep learning models with PyTorch.
- Data analysis skills to turn noisy measurements into conclusions you can defend.
- Judgment to turn an ambiguous performance question into a measurable one, and to prioritize what matters.
- Quantitative communication clear enough to influence another team’s priorities.


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Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know.
We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.
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.
For US candidates only, please visit E-Verify Notice and Participation and Right to Work
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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