GPU Performance Engineer
Job Description
- Exposure to graphics algorithms/concepts such as rasterization, programmable shading, texturing, etc.
- Programming experience in Graphics API such as OpenGL, Vulkan, Direct3D or CUDA.
- Develop performance models for Qualcomm’s family of GPUs with a strong focus on performance accuracy and SW engineering.
- Collaborate with architects on development of new GPU features and associated trade-off experiments across a wide range of GPU workloads in order to optimize performance, power and cost.
- Develop tests and micro-benchmarks to troubleshoot and validate the performance of the various GPU blocks including fixed function graphics pipelines, programmable shader processors and memory subsystem.
- Develop tools and scripts to improve performance data analysis and streamline workflows.
- Experience with GPU/CPU architecture and performance modeling.
- Strong C++ and Python programming skills.
- World-class health benefit options providing world-class coverage to employees and their eligible dependents.
- Programs designed to help employees build and prepare for a financially secure future.
- Self and family resources to help build emotional/mental strength and resilience, as well as define purpose.
- Wellbeing programs and resources offering support to help employees Live+Well and Work+Well.
Job Description
Job Posting Date
2025-11-05
Company:
Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > GPU ASICS Engineering
General Summary:
At Qualcomm, we believe in the power of technology. For decades, our innovations have transformed entire industries, improved billions of lives, and addressed many of society’s biggest challenges. With the world becoming increasingly connected, we have a tremendous opportunity to shape a better future. As an R&D engine that has revolutionized the way people connect, our approach to innovation is strategic and purposeful. We understand that the success of our business is fundamentally connected to the well-being of our world.
General Summary:
Our mission is to ship the very best integrated GPUs in the world, putting Qualcomm in a position of graphics and compute leadership, in all its businesses. We are looking for passionate GPU performance modeling engineers that will help shape the architecture of future Adreno GPUs for Qualcomm Snapdragon compute platforms across smartphones, Windows PCs and Chromebooks, virtual reality and augmented reality devices, and automotive solutions.
This role will be available across multiple locations - San Diego, Santa Clara and Austin and Boxborough and across all levels.
What you will be doing :
Develop performance models for Qualcomm’s family of GPUs with a strong focus on performance accuracy and SW engineering.
Collaborate with architects on development of new GPU features and associated trade-off experiments across a wide range of GPU workloads in order to optimize performance, power and cost.
Develop tests and micro-benchmarks to troubleshoot and validate the performance of the various GPU blocks including fixed function graphics pipelines, programmable shader processors and memory subsystem.
Develop tools and scripts to improve performance data analysis and streamline workflows
Key-qualifications:
- The team looks for wide range of level and experience, typically from 3 years to 20 years.
- Experience with GPU/CPU architecture and performance modeling.
- Strong C++ and Python programming skills.
- Exposure to graphics algorithms/concepts such as rasterization, programmable shading, texturing, etc highly desired.
- Programming experience in Graphics API such as OpenGL, Vulkan, Direct3D or CUDA is a plus
- Good communication and presentation skills and desire to work as a team player
Minimum Qualifications:
• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 6+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 5+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
