Work with a team of world-class researchers to design and implement compiler optimizations for AI accelerators targeting state-of-the-art LLMs (large language models). Develop compiler software for design space exploration to map AI applications to AI accelerators.

• Engage with other researchers to debate and discuss merits of existing and proposed compiler optimizations for AI accelerators.
• Prepare internal reports and presentations to summarize progress/blockers.
• Perform research and propose new concepts in compilers to exercise the computer architecture features.
• Implement the compiler optimizations to generate programs that exercise the computer architecture features.
• Evaluate the performance benefits using the software simulators across different use-cases and determine the hardware and software bottlenecks to improve performance.
• Performa cost-benefit analysis using the cost models and the simulator performance and propose changes to the hardware and software to improve the trade-offs.

Required Technical and Professional Expertise

• Applicants should be PhD & MS students pursuing graduate studies.
• Strong software engineering background, and
• Proficiency in C, C++ and Python programming,
• Proficiency in state-of-the-art deep-learning models (example large-language models for Generative AI applications).
• Strong background in AI accelerators architecture and compilers.

Preferred Technical and Professional Expertise

• Strong software engineering background, and
• Proficiency in C, C++ and Python programming,