Senior Machine Learning Engineer – AI/ML Compiler

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.

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: •     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-accomodations@qualcomm.com  or call Qualcomm's toll-free number found  here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able