Engineering Manager, Model Compiler

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.  

At Wayve, 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 the Engineering Manager for the ML Compiler team, you will lead the team responsible for compiling our driving model to run on various embedded GPUs and accelerators. Occupying a critical junction between machine learning and embedded systems, success in this role will directly contribute to Wayve’s ability to deploy models at scale into customer vehicles. In this role, you and your team will enable model inference on various embedded GPUs and accelerators, such as Nvidia, Qualcomm, Renesas and others.

Key responsibilities:

• You will manage a multi-disciplinary team of ML compiler and GPU kernel engineers, setting clear objectives and milestones
• Efficiently allocate resource and technical infrastructure to achieve programme objectives
• Build and grow your team as needed to support business objectives as we increase the scale of our deployments
• You will have opportunities to develop new skills, especially in model optimisation

About you  

In order to set you up for success as an Engineering Manager in ML Compilation at Wayve, we’re looking for the following skills and experience.  

Essential 

• Proven experience as an Engineer Manager delivering complex engineering projects
• Experience developing ML compilers and/or GPU kernels (e.g. TensorRT, MLIR, TVM, CUDA, OpenCL, etc)
• Excellent interpersonal and communication skills

Desirable 

• Experience with C++, Python and ML frameworks such as PyTorch
• Experience with ML deployment pipelines
• Experience with embedded SoCs used in automotive environments, e.g. Nvidia, Qualcomm, Renesas, etc

This is a full-time role based in our office in Sunnyvale.  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.  

#LI-AB1

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.