GPU Research Engineer

Qualcomm's GPU Hardware Architecture Team is looking for talented engineers to help advance state-of-the-art Virtual Reality (VR) and Augmented Reality (AR) 3D GPU capabilities. Through close collaboration with graphics driver developers, customers, system team and GPU design team you will help develop and design new GPU hardware features. For this role we expect a strong understanding of the GPU pipeline, memory/cache architectures, SW stacks, and processor behavior to allow cutting edge applications to provide a new user experience on tomorrows hardware. Ideally also have familiarity with 3D API's like Vulkan, OpenGLES and/or D3D.

Team responsibilities include: • Discover customer requirements for next gen AR/VR devices • Analyze and influence future GPU architectures • Validate GPU features through HW and SW simulation • Guide feature development through design and verification • Implement GPU compiler and driver features • Analyze and debug code generation issues • Implement 3D test applications to validate power, performance or quality concepts for new features

More background on our team: Qualcomm's GPU Architecture Team is responsible for the development of the worlds most advanced graphics processing unit (GPU). The Adreno GPU is part of Qualcomm's System on a Chip (SOC) platform found in mobile phones, virtual and augmented reality headsets, wearables, laptop computers and more. The highly motivated VR/AR Team has been responsible for the graphics HW at the heart of some of the most popular VR/AR offerings like Meta/Oculus Quest2 & 3 and Microsoft Hololens2. Our responsibilities include: forward looking architecture, research and design, tools, frameworks, compilers, display and GPU drivers. We work on advancing 3D rendering concepts for gaming, VR and AR through analysis of interactions between user experience, driver SW behavior and HW capabilities. Balancing performance, power and quality requirements across the SOC. Beyond traditional graphics, the GPU architecture team works on advancing machine learning, ray tracing, and enhanced developer tools to facilitate debugging, optimizing, and deploying applications for existing and new Qualcomm SOC based devices.