GPU/AI Power Performance Staff Engineer
Qualcomm · Bengaluru
- Experience4+ yrs
- SalaryNot disclosed
- Work modeunknown
- Levelsenior
- Posted15 Sept 2026
About Qualcomm
Qualcomm is hiring in Bengaluru in semiconductors electronics. This role looks for around 4+ years of experience.
Skills
- GPU power modeling
- GPU architecture
- Low-power ASIC optimization
- ASIC design and verification
The role
A GPU power performance engineer in a semiconductor engineering company develops GPU power models for AI workloads, evaluates architecture and microarchitecture, and uses data-driven analysis to optimize low-power ASIC designs. This person correlates workload characteristics with power behavior, studies architectural trade-offs, and collaborates on GPU roadmap decisions. Defining skills include GPU architecture, power modeling, and low-power ASIC optimization, alongside Python, C++, ML frameworks, PrimeTime PX, Power Artist, GPU drivers, and compiler development.
Full job description
Company
Qualcomm India Private Limited
Job Area
Engineering Group, Engineering Group > Systems Engineering
General Summary
Job DescriptionDevelop and maintain GPU power modeling and estimation for diverse AI workloadsAnalyze and evaluate GPU architecture/microarchitecture for performance and power optimizationsCollaborate with hardware, software, and ML teams to identify power bottlenecks and propose architectural or algorithmic optimizationsAnalyze AI workload characteristics and correlate them with power behavior across different GPU generationsContribute to architectural trade-off studies and influence GPU roadmap decisions with data-driven insightsMinimum Qualifications:Master's or PhD degree or equivalent in Computer Engineering, Computer Science, Electrical Engineering, or related field..2+ years of experience with ASIC design and verification2+ years of experience with low-power ASIC optimization
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.
Preferred Qualifications:5+ years of experience with advanced CPU/GPU architecture/microarchitecture design development5+ years of experience with low-power ASIC design techniquesExperience in Python, C++, and ML frameworks (e.g., TensorFlow, PyTorch)Experience with industry tools such as PrimeTime PX and Power ArtistExperience with Vulkan, DirectX3D, OpenGL, OpenCL, or Cuda developmentExperience with GPU driver and compiler developmentSkills: C/C++ Programming Language, Scripting (Python/Perl), Assembly, Verilog/SystemVerilo
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