Wayve
Tech Lead, GPU Kernel Engineer
Wayve - Sunnyvale, California, United States, 94087
Work at Wayve
Overview
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Overview
The role
As the Tech Lead for the GPU Kernel team, you’ll lead the strategic direction for Wayve’s GPU kernel development. This role occupies a critical junction between machine learning and embedded systems, enabling us to deploy our transformer-based driving models efficiently onto autonomous vehicles. This is an exciting opportunity to lead in several high impact, early stage projects at Wayve with the ultimate goal of enabling product deployments onto millions of customer vehicles around the world. Key responsibilities:
You will lead a multi-disciplinary team of GPU kernel engineers, breaking down large milestones into objectives which can be delivered by yourself and the team As a hands-on engineer, you will deliver critical roadmap milestones in enabling efficient inference on multiple target GPUs and accelerators You will work closely with members of the ML and Software teams to optimise models for deployment on edge You will have opportunities to develop new skills, especially in model optimisation About you
In order to set you up for success as a Tech Lead in ML Compilation at Wayve, we’re looking for the following skills and experience. Essential:
Proven experience as a technical lead or senior engineer on complex engineering projects Experience developing GPU kernels (e.g. CUDA, OpenCL, etc) Proficiency in C++ and ML frameworks such as PyTorch Excellent interpersonal and communication skills Ability to mentor and guide a team of engineers Desirable:
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
#J-18808-Ljbffr
As the Tech Lead for the GPU Kernel team, you’ll lead the strategic direction for Wayve’s GPU kernel development. This role occupies a critical junction between machine learning and embedded systems, enabling us to deploy our transformer-based driving models efficiently onto autonomous vehicles. This is an exciting opportunity to lead in several high impact, early stage projects at Wayve with the ultimate goal of enabling product deployments onto millions of customer vehicles around the world. Key responsibilities:
You will lead a multi-disciplinary team of GPU kernel engineers, breaking down large milestones into objectives which can be delivered by yourself and the team As a hands-on engineer, you will deliver critical roadmap milestones in enabling efficient inference on multiple target GPUs and accelerators You will work closely with members of the ML and Software teams to optimise models for deployment on edge You will have opportunities to develop new skills, especially in model optimisation About you
In order to set you up for success as a Tech Lead in ML Compilation at Wayve, we’re looking for the following skills and experience. Essential:
Proven experience as a technical lead or senior engineer on complex engineering projects Experience developing GPU kernels (e.g. CUDA, OpenCL, etc) Proficiency in C++ and ML frameworks such as PyTorch Excellent interpersonal and communication skills Ability to mentor and guide a team of engineers Desirable:
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
#J-18808-Ljbffr