Qualcomm Technologies, Inc.
Engineering Group, Engineering Group gt; Machine Learning Engineering
Today, more intelligence is moving to end devices, and mobile is becoming a pervasive AI platform. At the same time, data centers are expanding AI capability through widespread deployment of ML accelerators. Qualcomm envisions making AI ubiquitous - expanding beyond mobile and powering other end devices, data centers, vehicles, and things. We are inventing, developing, and commercializing power-efficient on-device AI, edge cloud AI, data center 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 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 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 impact 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
Ideal candidates for this position will demonstrate the following:
• Master's degree or equivalent in Engineering, Information Systems, Computer Science, or related field.
• 2+ years Hardware Engineering, Systems Engineering, or related work experience.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 5+ 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 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
**Ideal candidates for this position will demonstrate the following:**
• Ability to code in C++ and Python
• Experience in modeling hardware and workloads in order to extract performance and power estimates
• High-level hardware modeling experience preferred
• 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 hardware simulators
_Qualcomm i_ _s co_ _mmitted to hiring and supporting individuals with disabilities. Although this role has some expected physical activity, an inability to perform one or more of the listed physical requirements should not deter otherwise qualified applicants from applying. We will work with you throughout the application and onboarding process to provide reasonable accommodations. Examples of expected physical activity include: frequently transporting between offices, buildings, and campuses up to ½ mile; frequently transporting and installing equipment up to 5 lbs.; performing tasks at various heights (e.g., standing or sitting); monitoring and utilizing computers and test equipment for more than 6 hours a day; and continuous communication which includes the comprehension of information with colleagues, customers, and vendors both in person and_ _remotely._
**Applicants** : If you are an individual with a disability and need an accommodation during the application/hiring process, please call Qualcomm’s toll-free number found here (https://qualcomm.service-now.com/hrpublic?id=hr\_public\_article\_view&sysparm\_article=KB0039028) for assistance. Qualcomm will provide reasonable accommodations, upon request, to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. Qualcomm is an equal opportunity employer and supports workforce diversity.
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**EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.**
If you would like more information about this role, please contact Qualcomm Careers (http://www.qualcomm.com/contact/corporate) .
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
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