GPU Performance Modelling Architect

Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Systems Engineering

General Summary:

Drive architecture exploration and performance analysis for next-generation GPUs through modeling, simulation, and workload characterization. Partner with architecture, software, compiler, and hardware teams to influence design decisions using data-driven insights.

Key Deliverables

• Develop and maintain GPU performance models for architecture evaluation.

• Conduct Performance analysis of graphics and compute workloads to identify bottlenecks.

• Perform architectural trade-off studies to generate and defend performance projections.

• Bring up new workloads on Performance Models by fixing bugs and developing new features.

• Evaluate new features and provide recommendations to improve performance and efficiency.

• Build automation and analysis tools to improve modeling productivity.

Responsibilities

• Design and execute performance experiments and simulations.

• Conduct root-cause analysis and derive actionable architectural insights.

• Collaborate with cross-functional teams on feature development and optimization.

• Develop tools, workflows, and methodologies for performance analysis.

• Present findings and influence future architecture decisions.

Critical / Must-Have Skills

• Strong understanding of computer architecture

• Strong analytical, debugging, and problem-solving skills.

• Proficiency in C/C++ and Python.

• Experience with architectural simulators and performance prediction.

• Experience with performance analysis, profiling, and workload characterization.

• Strong verbal and written communication skills

Good-to-Have Skills

• GPU/CPU/Memory architecture and/or Graphics fundamentals.

• Good knowledge of modern 3D graphics pipelines and APIs (Vulkan/DX12/OpenGL).

• Experience building performance analysis tools and automation frameworks.

• Technical leadership and cross-functional collaboration experience.

Minimum Qualifications:

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

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