机器学习工程师，性能工具

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.

Key responsibilities

• Design and build reliable, self-service performance tools that scale across models, hardware targets, and development workflows.

• Shape how W

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.

• 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.

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.

• 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.

This is a full-time role based in-office. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.

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.