Staff ML Performance Engineer (Training Efficiency)

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SunnyvalePosted 5 weeks ago

Role Overview

Wayve is hiring a Staff ML Performance Engineer (Training Efficiency). This is a full-time role in Sunnyvale. Full responsibilities, required qualifications, and the apply link are listed in the description below.

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Job description

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

We are looking for a Staff ML Performance Engineer to join our Training Tech team working on optimizing large scale ML jobs to enable scaling our models to the next order of magnitude. A successful candidate will increase efficiency of training and inference workloads in order to allow Wayve to train larger models faster.

Key responsibilities:

Profile ML workloads to identify their bottlenecks, e.g. using NVIDIA Nsight Systems
Design and implement efficiency improvements to maximize MFU and throughput, e.g. parallelism, model compilation, mixed precision
Design and implement observability tools to identify bottlenecks and drive performance improvements, e.g. to track MFU, throughput, latency, etc
Design and implement benchmarking tools, e.g. to track efficiency gains or regressions
Collaborate closely with Research teams to integrate training efficiency improvements and create a culture of performance optimization

About you

In order to set you up for success in this role, we’re looking for the following skills and experience.

Essential

10+ years of industry experience driving performance engineering across ML systems, GPU compute infrastructure, distributed platforms or similar field.
Experience optimizing large scale jobs on GPU compute clusters.
Experience in working in platform teams and working with research teams.
Experience in writing, reporting, and tracking performance benchmarks in an open and accessible way.
Ability to write high quality, well-structured and tested Python code
BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience

Desirable

Experience working with concurrent, parallel and distributed computing.
Experience using NVIDIA NSight Systems or other system profilers.
Experience implementing GPU kernels (CUDA, Triton, etc).
Knowledge of computing fundamentals - what makes code fast, secure and reliable.

This role is a full-time role based in Sunnyvale, CA (hybrid) and the reasonably estimated salary for this role ranges from $336,400 to $359,000, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.

#LI-HH1

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.

About Wayve

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Frequently Asked Questions

How do I apply for the Staff ML Performance Engineer (Training Efficiency) position at Wayve?

Use the Apply button above to submit your application directly to Wayve. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.

Where is the Staff ML Performance Engineer (Training Efficiency) position at Wayve located?

This position is based in Sunnyvale. Wayve has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.

What does a Staff ML Performance Engineer (Training Efficiency) at Wayve earn?

Wayve has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.

When was the Staff ML Performance Engineer (Training Efficiency) role at Wayve posted?

This role was posted on June 3, 2026 (36 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.