Staff ML Performance Engineer (Training Efficiency)

Reposted 10 Days Ago
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Sunnyvale, CA, USA
In-Office
Expert/Leader
Artificial Intelligence • Transportation
The Role
Optimize large-scale ML training and inference workloads by profiling bottlenecks, implementing efficiency improvements (parallelism, mixed precision, compilation), building observability and benchmarking tools, and collaborating with research and platform teams to scale models and increase training throughput.
Summary Generated by Built In
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.



Skills Required

  • 10+ years industry experience in performance engineering across ML systems, GPU compute infrastructure, or distributed platforms
  • Experience optimizing large scale jobs on GPU compute clusters
  • Experience working in platform teams and collaborating with research teams
  • Experience writing, reporting, and tracking performance benchmarks
  • Ability to write high quality, well-structured and tested Python code
  • BS or MS in Machine Learning, Computer Science, Engineering, or related technical discipline (or equivalent experience)
  • Experience 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 (performance, security, reliability)

Wayve Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Wayve and has not been reviewed or approved by Wayve.

  • Healthcare Strength Private healthcare and access to therapy via Spill are part of the standard package. This indicates robust health support within the core offering.
  • Leave & Time Off Breadth Paid vacation, public holidays, and additional leave programs are explicitly listed. This breadth of time away supports work–life balance expectations.
  • Equity Value & Accessibility Cash plus equity is standard in offers at this growth stage. This provides ownership alongside salary with perceived upside tied to company momentum.

Wayve Insights

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The Company
HQ: London
200 Employees
Year Founded: 2017

What We Do

We're Wayve, a leading developer of embodied intelligence for autonomous vehicles. We use AI to pioneer a next-generation approach to self-driving: AV2.0, which enables fleet operators to unlock the benefits of AV technology at scale. Founded in 2017, Wayve is made up of a diverse team of experts in machine learning and robotics. We were the first to deploy AVs on public roads with end-to-end deep learning. Today, our teams are based in London and California, and we're testing AVs in cities across the UK. Inspired by our vision for a smarter, safer, more sustainable world, we're looking for people who are passionate about building breakthrough solutions to some of the world’s most important challenges. If you're looking for an exciting opportunity with a dynamic team, get in touch!

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