GPU AI Performance Engineer

About the role

GPU AI Performance Engineer at Qualcomm. Analyze and evaluate GPU architecture/microarchitecture for performance optimizations of AI workloads.

What you'll do

• Analyze and evaluate GPU architecture/microarchitecture for performance optimizations of AI workloads
• Work across the AI stack, from model graphs and inference runtimes down to GPU kernels and compiler IR
• Collaborate with hardware, software, and ML teams to identify performance bottlenecks and propose architectural or algorithmic optimizations
• Analyze AI workload characteristics and correlate their behavior across different GPU generations
• Contribute to architectural trade-off studies and influence GPU roadmap decisions with data-driven insights

What you need

• 6–11 yrs of experience
• C++
• Python
• Verilog
• C
• Perl
• Machine learning
• B.Tech or B.E. or B.Sc or BCA or M.Tech or PhD

Good to have

• LLMs
• TensorFlow
• PyTorch