Careers
Quick summary
- Work type
- On-site
- Location
- San Diego, CARaleigh, NC
- Posted
- 55 days ago
- Nearby
- 99+ roles within 25 mi
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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 Machine Learning Engineer at Qualcomm, you will join the AI Software team as a senior developer responsible for advancing the Qualcomm AI Runtime (QAIRT) delegate across ExecuTorch, ONNX Runtime, and LiteRT frameworks. Your daily tasks include designing and implementing graph compilation stacks to lower various IR formats to QAIRT APIs, collaborating with cross-functional teams to optimize AI model inference on edge devices using the QAIRT SDK, validating software performance through rigorous testing, and integrating agentic AI workflows to enhance development efficiency. The role requires expertise in C/C++/Python, foundational knowledge of machine learning, and experience with deep learning frameworks like TensorFlow or PyTorch. Familiarity with graph compilation technologies such as MLIR and ExecuTorch is a plus, along with an understanding of GenAI model architectures and embedded platform optimization techniques.
Skills
What you'll do
- Design and develop the graph compilation stack for ExecuTorch, ONNX Runtime, and LiteRT.
- Optimize AI inference performance on Qualcomm edge devices using QAIRT SDK.
- Validate software performance through detailed analysis of machine learning use cases.
- Automate testing and benchmarking activities using agentic AI frameworks like Claude Code.
- Collaborate with the AI Software team to integrate new capabilities into QAIRT.
What we're looking for
- 2+ years of software development experience using C/C++/Python
- Foundational knowledge of machine learning and deep learning
- Experience with at least one deep learning framework (TensorFlow, PyTorch, ONNX)
- Familiarity with graph compilation technologies like MLIR
- Experience optimizing AI models for embedded platforms
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