Careers
Quick summary
- Work type
- On-site
- Location
- San Diego, CA
- Posted
- 60 days ago
- Nearby
- 99+ roles within 25 mi
Market check
Salary context
How this pay compares to similar roles
This listing doesn't post a salary. Most similar roles pay $152,150–$208,800.
Based on 239 similar postings.
Employer
About Qualcomm
Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.
Qualcomm currently has 745 open roles on FindRole.
Listed pay typically runs $154,000–$231,000 across 423 roles with salary data.
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At a glance
TL;DR · Careers
As a Senior Software Engineer in Machine Learning at Qualcomm’s San Diego headquarters, you will join a dynamic team focused on advancing the Qualcomm AI Stack and developing cutting-edge SDKs for Snapdragon platforms. Your daily responsibilities include designing and implementing an AI orchestration framework to enable efficient execution of neural networks on Snapdragon chips, as well as validating software performance through rigorous testing. The role requires expertise in C/C++ and Python, with a preference for experience in machine learning frameworks like TensorFlow and PyTorch, and familiarity with low-level hardware interactions across various operating systems. You will contribute to public open-source projects and work with advanced neural network models such as QNN and SNPE, driving innovation in AI technology at scale.
Skills
What you'll do
- Develop the AI orchestration framework for Snapdragon platforms using C/C++ and Python.
- Implement software tools to enable efficient execution of neural networks on Qualcomm hardware.
- Design SDKs that facilitate the development of machine learning applications on Snapdragon chips.
- Analyze and validate performance and accuracy of developed software through detailed testing.
- Contribute to public open-source projects related to AI and machine learning frameworks.
What we're looking for
- 2+ years of software development experience in C/C++ and/or Python.
- Experience developing embedded applications interacting with OS and hardware.
- Proficiency with machine learning frameworks like TensorFlow, PyTorch, ONNX.
- Knowledge of neural network models including QNN, SNPE, QAIRT.
- Familiarity with large language models (LLM), large vision models (LVM).
- Contribution to public open-source projects preferred.
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