Senior Research Engineer, Machine Learning Systems (Toronto)

Company and Job Area Qualcomm Canada ULC – Engineering Group > Machine Learning Engineering – General Summary As a member of the Low Power AI solution team, you will play a critical role in deploying AI models on Qualcomm's low‑power AI accelerator. The position focuses on mapping high‑level machine learning operators to low‑level hardware instructions, involving graph transformation, scheduling, memory planning, individual operator implementation, quantization, and other optimization techniques. Your expertise in machine learning is expected to enhance inference efficiency and accuracy of different models on Qualcomm’s hardware architecture. Key Responsibilities Explore and prototype novel or emerging ML model architectures optimized for on‑device, low‑power inference, including vision, audio, and multimodal workloads. Drive model–hardware co‑design by aligning architectural choices, operators, dataflows, and memory behavior with Qualcomm’s low‑power AI accelerators. Design, evaluate, and refine quantization, mixed‑precision, sparsity, and compression techniques, with careful analysis of accuracy–performance–power trade‑offs. Develop and optimize computational graphs, including operator fusion, scheduling strategies, and memory‑aware execution. Conduct rigorous performance and accuracy investigations using profiling tools, hardware counters, and targeted experiments. Collaborate closely with compiler, runtime, and hardware teams to convert exploratory prototypes into production‑viable execution paths. Influence future accelerator features, compiler capabilities, and deployment strategies through technical insights and experimental results. Required Skills & Experience Strong track record in machine learning research or advanced applied ML development, with demonstrated focus on inference efficiency. Deep understanding of ML model architecture, operator behavior, and inference‑time performance characteristics. Hands‑on experience with quantization and reduced‑precision inference (e.g., INT8/INT4, FP8/FP4, mixed precision, PTQ/QAT). Proven ability to prototype, analyze, and iterate on ideas under strict compute, memory, and power constraints. Proficiency in Python and C/C++, with comfort working across modeling, systems, and low‑level execution layers. Strong background in computer architecture and hardware‑aware optimization, particularly for AI accelerators. Ability to reason about computational graphs, tensor layouts, and memory movement at a detailed level. Preferred Qualifications Master’s degree or PhD in Computer Science, Engineering, Information Systems, or a related field. 1+ year of experience in Hardware Engineering, Software Engineering, Systems Engineering, or a related area (or 1+ year for PhD). Experience targeting or co‑designing for custom accelerators, NPUs, DSPs, or GPUs. Familiarity with compiler‑assisted ML optimization, graph transformations, or operator scheduling. Experience with multimodal or sensor‑driven models. Evidence of technical leadership, such as driving complex investigations, publishing, patenting, or shaping internal technical direction. Comfort operating in ambiguous, research‑heavy problem spaces with minimal upfront specification. Minimum Qualifications Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of relevant work experience. Master’s degree in the same fields and 1+ year of relevant work experience. PhD equivalent and 1+ year of relevant work experience. Equal Opportunity & Accommodations Qualcomm is an equal chance employer. If you are an individual with a disability and need an accommodation during the application/hiring process, Qualcomm is committed to providing an accessible process. You may e‑mail disability‑ or call Qualcomm’s toll‑free number. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to participate in the hiring process. Pay Range and Other Compensation $114,400.00 – $164,400.00 The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Salary is only one component of total compensation. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants. In addition, our highly competitive perks package is designed to support your success at work, at home, and at play. #J-18808-Ljbffr Apply on Kit Job: kitjob.ca/job/2pu73f