NPU/AI Processor PnP Benchmarking Engineer

Qualcomm India Private Limited is seeking an NPU/AI Processor PnP Benchmarking Engineer with 12-16 years of experience in post-Si Power and Performance Validation, preferably with AI/ML workloads. The role involves measuring and comparing NPU power and performance on Qualcomm and competitor chipsets, analyzing bottlenecks, and running AI/ML benchmarks. Candidates should have a strong understanding of NPU architecture, ML trends, and programming skills in C, C++, Perl, Python, Shell, Make file TCI.

Must Have

• 12-16 years of experience in post-Si Power and Performance Validation (preferably AI/ML workloads)
• Run workloads across Qualcomm and competitor products & compare power and performance
• Responsible for Running AI/ML Benchmarks, collecting results and coalescing them, analyzing bottlenecks across platforms
• Good understanding of NPU architecture, ML workloads
• Experience in silicon measurements and validation knowledge
• Fundamental understanding of latest ML trends, transformers, quantization, fixed/floating point
• Understand the software stack to launch, run, and teardown applications in the Windows, Android, and Auto Space
• Understand all the system settings (clock, voltage, thermal, system settings etc.) that can impact the performance of ML applications
• Programming/Scripting Skills — C, C++, Perl, Python, Shell, Make file TCI
• Strong troubleshooting, analytical and debug skills

Perks & Benefits

• World-class health benefit option providing world-class coverage to employees and their eligible dependents
• Programs designed to help employees build and prepare for a financially secure future
• Self and family resources to build emotional/mental strength and resilience, as well as define purpose
• Wellbeing programs and resources to help employees Live+Well and Work+Well

Job Description

Job Area:

Engineering Group, Engineering Group > Systems Engineering

General Summary:

Job Summary:

• 12 – 16 years of experience in post-Si Power and Performance Validation (preferably AI/ML workloads) on complex CPU/GPU/NPU chipsets/Ips.
• Run workloads across QCOM and other competitor products & compare power and performance.
• QDSP team is responsible for delivering high-performance NSP (neural signal processor) cores which are at the heart of Qualcomm's multi-tier SoC roadmap targeted for mobile space.
• Qualcomm is the largest fabless design company in the world, generating over $15 Billion in annual revenues from chipsets and royalties from intellectual property. Qualcomm provides hardware, software and related services to nearly every mobile device maker and operator in the global wireless marketplace.

Job Responsibilities:

• In this highly visible and interactive role, your primary responsibility will be to measure the power and performance of NPU on Qualcomm and other competitor chipsets, compare the same.
• Responsible for Running AI/ML Benchmarks, collecting results and coalescing them, analyzing bottlenecks across platforms.
• Involves having a good understanding of NPU architecture, ML workloads etc.
• Experience in silicon measurements and validation knowledge.

Skillset/Experience:

• 12-16 years’ experience in NSP/Processor/ASIC performance and power validation.
• Experience in application performance analysis /identify bottlenecks.
• Fundamental understanding of latest ML trends, transformers, quantization, fixed/floating point etc.
• Understand the software stack to launch, run, and teardown applications in the Windows, Android, and Auto Space
• Good understanding of ML workloads.
• Understand all the system settings (clock, voltage, thermal, system settings etc.) that can impact the performance of ML applications.
• Programming/Scripting Skills — C, C++, Perl, Python, Shell, Make file TCI.
• Strong troubleshooting, analytical and debug skills
• Should have excellent inter-personal, communication skills and ability to work in a fast-paced exciting environment.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.

OR

• Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.

OR

• PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.