Machine Learning Performance Architecture Engineer (All Levels) (BB-26E4F)

Found in: Talent CA

Job Overview: Qualcomm is a company of inventors that unlocked 5G ushering in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform 5Gs potential into world-changing technologies and products. This is the Invention Age - and this is where you come in. Today, more intelligence is moving to end devices, and mobile is becoming the pervasive AI platform. Building on the smartphone foundation and the scale of mobile, Qualcomm envisions making AI ubiquitous - expanding beyond mobile and powering other end devices, machines, vehicles, and things. We are inventing, developing, and commercializing power-efficient on-device AI, edge cloud AI, and 5G to make this a reality. We are looking for Performance Architecture Engineers to drive performance and power enhancements into the HW and SW stacks of state-of-the-art machine learning solutions. The Performance Architecture team is comprised of experts that span the full gamut from software architecture, algorithm development, kernel optimization, down to hardware accelerator block architecture and SOC design. The ideal candidate will augment the team by contributing to one or many of these areas. Machine Learning Performance Architecture Engineer Responsibilities: Understand trends in ML network design, through customer engagements and latest academic research, and determine how this will affect both SW and HW design Analyze ML/AI algorithms and workloads on exploratory and existing Qualcomm HW and SW stacks through event-driven simulation and on-device characterization Define, model and tune algorithms for ML/AI compilers, kernels and HW features to improve mappings of ML/AI workloads on existing and future HW Contribute new and evolutionary features to even-driven models of HW and SW Pre-Silicon prediction of performance for various ML algorithms Perform analysis of performance/area/power trade-offs for future HW and SW ML algorithms including inpact of SOC components (memory and bus impacts) On-device correlation and tuning of algorithm versus pre-silicon predictions Implementing SW algorithms for mapping ML/AI workloads on Qualcomm HW Contribute to the creation of debug and analysis tools Interface with other cross-site and cross-functional teams to arrive at best-in-class algorithms Minimum Requirements: Bachelor's degree or equivalent in Engineering, Information Systems, Computer Science, or related field. 2+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience. Preferred Skills and Experience: Ability to code in C++ and Python Strong background in algorithm development and analysis is essential Strong software engineering principles are essential Strong communication skills (written and verbal) Detail-oriented with strong problem-solving, analytical and debugging skills Demonstrated ability to learn, think and adapt in a fast-changing environment Preferred exposure to front-end ML frameworks (i.e.,TensorFlow, PyTorch, ONNX) Experience in compiler design and development is an asset Knowledge of different classes of ML models (i.e. CNN, RNN, etc) is an asset Knowledge of computer architecture, digital circuits and event-driven simulators Knowledge of transaction level modelling is an asset. On-silicon debug skills of high-performance compute algorithms is an asset

calendar_today2 days ago


info Full time

location_on Markham, Canada

work Qualcomm

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