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Qualcomm

Quick summary

Work type: On-site
Location: San Diego, CA
Posted: 40 days ago
Closes: Oct 24, 2026
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $211k

$162k most similar roles pay here $267k

This listing doesn't post a salary. Most similar roles pay $174,950–$246,150.

Based on 240 similar postings.

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About Qualcomm

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

Qualcomm currently has 270 open roles on FindRole.

Listed pay typically runs $154,000–$231,000 across 196 roles with salary data.

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At a glance

TL;DR · Careers

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Join Qualcomm Technologies as an AI Performance System Software Engineer on the Snapdragon team to enhance performance and power efficiency across software and hardware stacks for cutting-edge machine learning solutions. You will collaborate with development leads and architects to optimize SDKs, tools, and documentation, ensuring Windows application developers achieve top-tier performance through automated workflows. Key responsibilities include analyzing ML/AI algorithms, developing comprehensive benchmark tests, tuning workloads on Snapdragon’s NPU, GPU, and CPU, and contributing to future SoC designs. Ideal candidates possess 1-2 years of experience in optimizing AI for GPUs or NPUs, knowledge of TensorFlow, PyTorch, ONNX, and strong skills in C++, Python, and software engineering principles.

Skills

Python C++ C TensorFlow PyTorch ONNX GPU NPU CPU Computer_Vision Audio Generative_AI Linux Windows CI/CD

What you'll do

Understand ML network design trends and their impact on SW and HW.
Analyze ML/AI algorithms and workloads using Qualcomm stacks and tools.
Develop comprehensive AI benchmark tests for Windows on Snapdragon.
Tune ML/AI algorithms to improve performance on NPU, GPU, CPU.
Contribute new features to reduce performance bottlenecks in future SoCs.

What we're looking for

Experience in optimizing AI performance on GPU, NPU, and CPU.
Knowledge of state-of-the-art AI models in domains like Computer Vision, Audio, or Generative AI.
Proficiency in C, C++, and Python programming languages.
Understanding of computer architecture and embedded systems implementation.
Ability to develop and implement improvements into the SW stack including SDKs and tools.
Strong software engineering principles and problem-solving skills.
Experience with ML frameworks such as TensorFlow, PyTorch, or ONNX.

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