Modular is hiring a
Senior AI GPU Performance Engineer

Summary

Join Modular as an AI GPU Performance Engineer to architect performance libraries for GPUs, develop kernels and algorithms to increase performance of kernels, reduce activation volumes, speedup data pre- and post-processing, and improve end-to-end performance of the AI workloads. Collaborate with cross-functional teams to analyze and optimize AI performance on diverse GPU architectures across the stack.

Requirements

• Deep understanding of GPU computer architecture (memory hierarchies, tensor-cores, etc.) and their impact on algorithm design
• 10+ years of relevant experience working with modern software systems and use of design patterns
• Self motivation with the ability to design, communicate and lead new projects
• Experience with GPU programming languages such as CUDA or OpenCL
• Familiarity with GPU assembly such as PTX and SASS
• Knowledge of SOTA frameworks such as CUTLASS, TRTLLM, Triton, etc
• Able to identify industry trends, analyze emerging technologies and disruptive paradigms

Responsibilities

• Design, develop, and optimize high-performance AI numeric and data manipulation kernels/operators for GPUs
• Achieve state-of-the-art performance by leveraging software and micro-architectural features of GPUs
• Work with compiler, framework, runtime, and serving teams to deliver end-to-end performance that fully utilizes GPU workstations and servers
• Collaborate with machine learning researchers to guide system development for future ML trends
• Engage in prototyping exercises to quantify the value proposition and develop execution plans

Benefits

• Premier insurance plans
• Up to 5% 401k matching
• Very generous WFH setup stipends
• Flexible paid time off