Senior Machine Learning Engineer – AI​/ML Compiler

Company:

Qualcomm Technologies, Inc.

Engineering Group, Engineering Group >
Machine Learning Engineering

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.

• 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.
• 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.
• PhD in Computer Science, Engineering, Information Systems, or related field.

• 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, Execu Torch, 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

• 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.

• Works independently with minimal supervision.
• Decision-making may affect work beyond immediate work group.
• Requires verbal and written communication skills to convey information. May require basic negotiation, influence, tact, etc.
• Has a moderate amount of influence over key organizational decisions (e.g., is consulted by senior leadership to make key decisions).
• Tasks require multiple steps which can be performed in various orders; some planning, problem-solving, and prioritization must occur to complete the tasks effectively.

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e‑mail disability‑ or call Qualcomm's toll‑free number found here. Upon request, Qualcomm will provide reasonable accommodations to support…