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.

The Cloud AI Architecture team is comprised of experts that span the full gamut from performance modeling, software architecture, algorithm development, kernel optimization, down to hardware accelerator block architecture and SOC design. 

We are looking for an AI Accelerator Architect who would lead a team developing performance models that accurately estimate workload performance and power characteristics given known AI architectures.   This team also executes developed models against various workloads. These models will be used to estimate performance for various internal teams and external customers.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ 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 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Responsibilities:

Define and develop performance models designed to estimate performance and power usage of AI workloadsLead a team of performance architects, providing guidance for performance studies and model enhancementsExecute models against requested workloads and configurationsUnderstand trends in ML network design through customer engagements and latest academic research and determine how this will affect both SW and HW designWork with customers to understand workloads and performance requirementsAnalysis of current accelerator and GPU architecturesSuggest hardware enhancements required for efficient execution of AI workloadsPre-Silicon prediction of performance for various ML training workloadsPerform analysis of performance/area/power trade-offs for future HW and SW ML algorithms including impact of SOC components (memory and bus impacts)

Minimum Requirements:

Master's degree or equivalent in Engineering, or related field.8+ years Hardware Engineering, Systems Engineering, or related work experience.3+ years experience performance modeling of AI accelerators or similar systemsTeam leadership experienceIn-depth knowledge of nVidia/AMD GPGPU capabilities and architecturesKnowledge of LLM architectures and their HW requirements

Preferred Skills and Experience:

Knowledge of computer architecture, digital circuitsKnowledge of modeling of communication systemsKnowledge of communication protocols used in AI systemsUnderstanding of Network-on-Chip (NoC) designs used in System-on-Chip (SoC) designsUnderstanding of various memory technologies used in AI systemsHigh-level architectural-level hardware modeling experience preferredKnowledge of AI Inference and Training systems such as NVIDIA DGX and NVL72Strong communication skills (written and verbal)Detail-oriented with strong problem-solving, analytical and debugging skillsGood leadership abilities with attention given to tracking tasks and ensuring timely completion of those tasksProficient in Excel including VBA scriptingDemonstrated ability to learn, think and adapt in a fast-changing environmentAbility to code in C++ and PythonUnderstanding of elemental operations performed in ML workloads

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 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).

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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.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

 

Pay range and Other Compensation & Benefits:

$180,700.00 - $271,100.00

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.