Qualcomm
Graphics Performance Verification, Principal
Qualcomm, San Diego, California, United States, 92154
Please read the following job description thoroughly to ensure you are the right fit for this role before applying.Company:
Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > GPU ASICS Engineering
General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm GPU Engineer, you may architect, design, implement, verify, and/or optimize the performance and power of GPU cores. Qualcomm Engineers collaborate with cross-functional teams to meet and exceed customer needs.
Minimum Qualifications:
Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 8+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
OR Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 7+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
OR PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 6+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
Responsibilities:
Responsible for pre-silicon performance analysis and closure on state of art GPU design using trending graphic/compute/AI benchmarks. Work closely with design/arch/model teams on GPU pipeline bottleneck analysis and propose hw/sw optimizations to improve PPA.
Contribute to pre-silicon execution with additional benchmark functional coverage.
Virtual GPU bring-up using hardware accelerated emulation system to enable other sw/hw teams on pre-silicon functional execution.
Analysis of performance and architectural bottlenecks in the GPU designs.
Work with GPU Design and Architecture Teams to understand concepts and performance bottlenecks in GPU.
Implement data analytics using Python.
HW-SW co-verification, simulation, simulation-acceleration, emulation, benchmark analysis, big-data analytics are all tools in our verification toolbox you will use on a daily basis.
Skills and Experience We Would Love to See:
GPU pipeline, System Verilog, Python, C/C++ skills required.
Desirable Qualifications:
Overall 15+ years of experience.
Experience with GPU Architectures and pipeline analysis.
RTL design experience and/or very strong SoC architecture background.
Experience with Simulation Acceleration and Emulation.
Experience working with System Level Architecture Teams to understand Performance Requirements and Bottlenecks.
Experience with SW and HW design partitioning.
Experience with analyzing performance issues in Software and Hardware.
Data analysis using Python and Data Visualization.
Pay Range:
$216,000.00 - $324,000.00
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. 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!
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Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > GPU ASICS Engineering
General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm GPU Engineer, you may architect, design, implement, verify, and/or optimize the performance and power of GPU cores. Qualcomm Engineers collaborate with cross-functional teams to meet and exceed customer needs.
Minimum Qualifications:
Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 8+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
OR Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 7+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
OR PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 6+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
Responsibilities:
Responsible for pre-silicon performance analysis and closure on state of art GPU design using trending graphic/compute/AI benchmarks. Work closely with design/arch/model teams on GPU pipeline bottleneck analysis and propose hw/sw optimizations to improve PPA.
Contribute to pre-silicon execution with additional benchmark functional coverage.
Virtual GPU bring-up using hardware accelerated emulation system to enable other sw/hw teams on pre-silicon functional execution.
Analysis of performance and architectural bottlenecks in the GPU designs.
Work with GPU Design and Architecture Teams to understand concepts and performance bottlenecks in GPU.
Implement data analytics using Python.
HW-SW co-verification, simulation, simulation-acceleration, emulation, benchmark analysis, big-data analytics are all tools in our verification toolbox you will use on a daily basis.
Skills and Experience We Would Love to See:
GPU pipeline, System Verilog, Python, C/C++ skills required.
Desirable Qualifications:
Overall 15+ years of experience.
Experience with GPU Architectures and pipeline analysis.
RTL design experience and/or very strong SoC architecture background.
Experience with Simulation Acceleration and Emulation.
Experience working with System Level Architecture Teams to understand Performance Requirements and Bottlenecks.
Experience with SW and HW design partitioning.
Experience with analyzing performance issues in Software and Hardware.
Data analysis using Python and Data Visualization.
Pay Range:
$216,000.00 - $324,000.00
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. 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!
#J-18808-Ljbffr