Senior Machine Learning Engineer – AI/ML Compiler

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Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary:

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field.

Preferred Qualifications:

• 3+ years of industry experience in ML infrastructure, compiler engineering, or AI framework development
• Proficient in Python and C++
• Solid understanding of ML compiler concepts (graph IRs, operator fusion, shape inference, lowering passes, backend partitioning) and hands-on experience with one or more compiler stacks such as MLIR, ONNX, or TVM
• Experience with PyTorch model export (torch.export, torch.compile, FX, ATen IR) and on-device deployment frameworks such as LiteRT, ExecuTorch, or ONNXRuntime
• Familiarity with SoC-level constraints (memory bandwidth, compute precision, NPU/DSP execution) and hardware-specific runtimes such as QAIRT/QNN is a plus
• Experience building automated CI/CD pipelines for model compilation and validation at scale
• Strong written and verbal communication skills; proficiency with git and software engineering best practices Principal Duties and Responsibilities:- Build & maintain machine learning compiler technologies that turn AI models (from PyTorch or ONNX) into efficient code that runs on device chips (CPU, GPU, and NPU processors). - Contribute to AI hub compiler, ONNX Runtime QNN —doing graph optimization, partitioning, and making sure models work correctly across backends. - Build debugging tools to spot and fix failures, accuracy loss, or slowdowns, with clear diagnostics for other developers. - Solve open-ended problems independently while mentoring teammates and giving technical guidance. - Explain complex compiler ideas clearly to chip engineers, business partners, and outside developers.Level of Responsibility: