Staff Machine Learning Performance Engineer, Inference Optimisation
Wayve
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.
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
As a Staff/Principal ML Performance Engineer, you’ll lead high impact projects optimising ML inference for edge accelerators and GPUs. The focus of this team is to run large transformer-based models efficiently in low-cost, low-power edge devices to enable Wayve’s first driving product. This is an exciting opportunity to lead in several high impact, early stage projects at Wayve, operating at the intersection of ML Compilers, Kernels, and ML engineering.
Key responsibilities:
- You’ll identify opportunities for improvement in the ML compiler and/or kernels and implement
- Develop with multiple target platforms in mind e.g. Nvidia (Thor, Orin), Qualcomm, etc
- You’ll build technical roadmaps and work with teams to execute against them
- You’ll collaborate closely with model developers and software engineers in other teams across the business
- You’ll have the opportunity to develop new skills and experience
About you
Essential
- Experience solving optimisation problems (e.g. developing systems with latency or other resource constraints)
- Experience with any of (or similar): MLIR, TensorRT, Cuda, Qualcomm QNN, Cuda, OpenCL, Triton
- Experience leading technical teams (5+ people)
- Strong engineering background
- Excellent interpersonal and communication skills
Desirable
- Experience with Nvidia and Qualcomm SoCs and frameworks are valuable, but not required
- Experience in ML development is valuable, but not required
- Proficiency with Python/C++
This is a full-time role based in our office in London 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. We operate core working hours so you can determine the schedule that works best for you and your team.
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.
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.