GPU Compute & MLIR Compiler Principal Engineer — AI Workloads

Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Systems Engineering

General Summary:

• Drive technical direction and execution of AI and Generative AI workloads on GPU platforms.
• Lead exploration and optimization of emerging workloads including LLMs, transformer-based models, computer vision, and other AI/ML applications.
• Collaborate across architecture, compiler technologies and frameworks such as TVM, MLIR, and IREE, software, performance, and product teams to drive solutions from early exploration through product-quality implementation.
• Provide technical leadership, conduct design reviews, and mentor engineers working across GPU AI initiatives.
• Develop and optimize GPU solutions leveraging capabilities such as matrix acceleration, mixed-precision computation, quantization, and other hardware acceleration features.
• Analyze end-to-end AI workload performance and identify bottlenecks across models, frameworks, compilers, runtimes, GPU kernels, and hardware architecture.
• Drive compiler and runtime optimizations to improve AI workload performance, power efficiency, and scalability.
• Evaluate emerging AI models, algorithms, frameworks, and optimization techniques and assess their implications for future GPU architectures.
• Work closely with GPU architecture teams to translate workload analysis into actionable recommendations for future architectural capabilities.
• Develop prototypes and proof-of-concepts to evaluate new ideas and demonstrate GPU capabilities for AI workloads.
• Communicate technical findings, trade-offs, recommendations, and results effectively to both engineering and leadership audiences

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.

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.

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