About the position

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content. The GPU/AI System Technology and Engineering Team is committed to developing highly optimized OS and system software to support deep learning and high-performance computing (HPC) workloads in large-scale data centers. We focus on delivering core software components for the next generation of AI and HPC platforms, benchmarks, and fine-tuning performance. Our work spans the entire hardware/software stack, from GPU drivers to deep learning frameworks, to ensure peak performance across all layers. By joining this team, you will work with the best engineers and talents in this industry and have a broad opportunity to get in touch with the latest AI application systems and newly emerged technology in computing, networking and storage. You will gain remarkable GPU architecture, system software development and GPU validation experience in the most advanced hardware infrastructure on a massive scale. Internships at ByteDance aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. This Internship Program runs for 12 weeks beginning in May/June 2025. Successful candidates must be able to commit to one of the following summer internship start dates below: Monday, May 12, Monday, May 19, Tuesday May 27 (Memorial Day May 26), Monday, June 9, Monday, June 23.

Responsibilities

  • Design and implement performance benchmarks and testing methodologies to evaluate system performance
  • Develop benchmark tools and performance optimization of AI workloads specifically tailored for large-scale LLM training and inference, as well as High-Performance Computing (HPC)
  • Develop Python scripts to automate the testing of various benchmark tools
  • Collaborate with internal teams to identify system bottleneck, debug and improve performance issues.
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