Qualcomm
Senior Machine Learning Performance Architect
Qualcomm, San Diego, California, United States, 92189
Company:
Qualcomm Technologies, Inc. Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering General Summary:
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 Performance modeling, algorithm development, kernel optimization, hardware accelerator architecture and SOC design. The ideal candidate will augment the team by contributing to one or many of these areas. Minimum Qualifications:
• Bachelors 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 • Masters 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. Machine Learning Performance Architecture Engineer Responsibilities:
Develop and enhance performance models that will accurately predict performance and power consumption for various AI workloads 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 Interface with other cross-site and cross-functional teams to arrive at best-in-class algorithms Minimum Requirements:
Masters degree or equivalent in Engineering, Information Systems, Computer Science, or related field. 2+ years Hardware Engineering, Systems Engineering, or related work experience. Preferred Skills and Experience:
Ability to code in Python Proficiency in Excel including VBA scripting Experience in modeling hardware and workloads in order to extract performance and power estimates Architectural-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. LLM, LVM, CNN, etc) Knowledge of computer architecture, digital circuits and hardware simulators EEO and Accommodations:
Qualcomm is an equal opportunity 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 email disability-accommodations@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 participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Pay range and Other Compensation & Benefits: $126,700.00 - $217,900.00 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. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link. If you would like more information about this role, please contact Qualcomm Careers.
#J-18808-Ljbffr
Qualcomm Technologies, Inc. Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering General Summary:
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 Performance modeling, algorithm development, kernel optimization, hardware accelerator architecture and SOC design. The ideal candidate will augment the team by contributing to one or many of these areas. Minimum Qualifications:
• Bachelors 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 • Masters 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. Machine Learning Performance Architecture Engineer Responsibilities:
Develop and enhance performance models that will accurately predict performance and power consumption for various AI workloads 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 Interface with other cross-site and cross-functional teams to arrive at best-in-class algorithms Minimum Requirements:
Masters degree or equivalent in Engineering, Information Systems, Computer Science, or related field. 2+ years Hardware Engineering, Systems Engineering, or related work experience. Preferred Skills and Experience:
Ability to code in Python Proficiency in Excel including VBA scripting Experience in modeling hardware and workloads in order to extract performance and power estimates Architectural-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. LLM, LVM, CNN, etc) Knowledge of computer architecture, digital circuits and hardware simulators EEO and Accommodations:
Qualcomm is an equal opportunity 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 email disability-accommodations@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 participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Pay range and Other Compensation & Benefits: $126,700.00 - $217,900.00 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. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link. If you would like more information about this role, please contact Qualcomm Careers.
#J-18808-Ljbffr