Qualcomm International Inc., Mexico Branch Office

Senior Machine Learning Engineer – AI/ML Compiler at Qualcomm International Inc., Mexico Branch Office

Department: Machine Learning Engineering

Compensation

$151,200 – $226,800/yr

Setup: On-site
Location: California
Type: Full-time
Level: senior
Posted: Sep 17, 2026

Description

Qualcomm is hiring a Machine Learning Engineer to build and maintain machine learning compiler technologies that convert PyTorch or ONNX models into efficient code for CPU, GPU, and NPU device chips. The role contributes to AI hub compiler and ONNX Runtime QNN, performs graph optimization and partitioning, develops debugging and diagnostic tools, and mentors teammates. It requires a bachelor's, master's, or PhD in a relevant field plus the specified work-experience alternatives, with Python, C++, compiler, PyTorch, and on-device deployment expertise preferred. The listed pay range is $151,200 to $226,800.

Required Skills

Python
C++
ML compilers
PyTorch
ONNX Runtime
Graph optimization
Git

Additional Information

Minimum Education: Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, with 2+ years of relevant work experience; alternatively, a master's degree with 1+ year of relevant experience, or a PhD in a related field.
Required Previous Experiences: 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience
1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience
Preferred Qualifications: 3+ years of industry experience in ML infrastructure, compiler engineering, or AI framework development
Proficiency in Python and C++
Understanding of ML compiler concepts and hands-on experience with MLIR, ONNX, or TVM
Experience with PyTorch model export and on-device deployment frameworks
Familiarity with SoC-level constraints and QAIRT/QNN hardware runtimes
Experience building automated CI/CD pipelines for model compilation and validation
Strong communication skills and proficiency with Git and software engineering best practices