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.  Join our world-class team as we tackle today's most complex challenges and 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.   Make Wayve the experience that defines your career!  

The Role

As an Embedded Kernel Engineer within our dynamic team, you'll be instrumental in deploying Wayve's autonomous vehicle (AV) AI model across consumer vehicles. Your role is crucial in developing model compilers and crafting high-performance kernels for efficient inferencing on embedded GPU environments. Through close collaboration with machine learning engineers, you'll pinpoint opportunities to amplify inference performance by optimally utilizing the hardware capabilities of various deployment platforms. Your deep understanding of GPU architecture, from memory management to the intricacies of GPU cores, will be pivotal. Utilizing tools like TensorRT and model compilers, you will push the boundaries of what's possible in inference performance in the embedded environment.

Key responsibilities:

  • Optimization Leadership: Lead efforts to discover the optimal model compilation strategies that harmonize compute intensity, caching, and memory bandwidth to maximize hardware utilization on targeted platforms
  • Precision Transformation: Innovate in transforming large AI models to low precision implementations, ensuring minimal accuracy loss
  • GPU Architecture Mastery: Become the go-to authority on GPU architecture for targeted hardware platforms, such as NVIDIA Orin or Qualcomm Snapdragon
  • Model Compilation Process Creation: Design and implement the process to convert AI models from a PyTorch framework to native platform-specific programs, enhancing model efficiency and performance

About you

Essential

  • Advanced C++ Skills: Proficiency in C++ programming, with a demonstrated history of developing efficient, high-quality code.
  • GPU Development Expertise: A minimum of 5 years of direct experience in developing kernels for GPUs, showcasing an ability to solve complex computational challenges.
  • GPU Programming Tools Proficiency: Extensive experience with GPU programming using tools like CUDA and TensorRT, specifically within embedded environments.
  • Deep GPU Design Knowledge: A thorough understanding of GPU design and operations, including familiarity with AI accelerators.
  •  

Desirable

  • Educational Qualifications: A Master's degree in a relevant field, supplemented by research experience.
  • Quantization and Compiler Experience: Expertise in model quantization, particularly in implementing low precision formats, and experience with developing and using model compilers.

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.

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.  

For more information visit Careers 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.



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