GPU Kernel Development Engineer

Qualcomm

Confirmed live today High trust

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$123,700–$185,500 / yr
Posted
40 days ago
Freshness
Confirmed live today
Closes
Mar 16, 2027

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $216k
This role $155k
$107k $280k
below market most similar roles pay here above market

This role pays less than 96% of similar roles. Most pay $193,476–$238,875 — the blue band above. At the midpoint, this role pays about $155k versus about $216k for comparable roles.

Based on 240 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 575 open roles on FindRole.

Listed pay typically runs $147,900–$221,900 across 550 roles with salary data.

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At a glance

TL;DR · GPU Kernel Development Engineer

The GPU Kernel Development Engineer joins the GPU Software team to develop high-performance kernels and runtimes for accelerating GPGPU operations like Machine Learning and Image Processing. This role involves optimizing Adreno GPU drivers for standard APIs including OpenCL, OpenGL ES, Vulkan, and DirectX across Android, Linux, and Windows platforms. You will accelerate Machine Learning operations for inference and training, develop runtimes and frameworks, and collaborate with hardware designers to improve hardware and software interfaces. Key responsibilities include writing code in C, C++, and Python, creating unit tests, and producing technical documentation. Required skills include strong C/C++ programming, familiarity with GPGPU APIs like CUDA or OpenCL, and an understanding of data structures, algorithms, and object-oriented programming to solve complex graphics and processing problems.

What you'll do

  • Develop and optimize high-performance kernels and runtimes for GPGPU operations like Machine Learning and Image Processing.
  • Write code for device drivers and APIs using C, C++, and Python.
  • Accelerate Machine Learning operations for both inference and training on the GPU.
  • Optimize Adreno GPU drivers for standard APIs including OpenCL, OpenGL ES, Vulkan, and DirectX.
  • Collaborate with hardware designers to understand, improve, and document hardware/software interfaces.
  • Write detailed design documentation, feature descriptions, and technical samples.
  • Develop unit tests to ensure software quality and reliability.

What we're looking for

  • Bachelor's degree in a related field and 2+ years of relevant engineering experience.
  • Master's degree in a related field and 1+ year of relevant engineering experience.
  • PhD in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or a related field.
  • 1+ year of academic and/or work experience with a programming language suitable for graphics, such as C or C++.
  • Strong C/C++ programming skills.
  • Familiarity with a GPGPU API such as CUDA or OpenCL.
  • Understanding of data structures, algorithms, and object-oriented programming.
  • Knowledge of Machine Learning Theory (preferred).

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