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Software Engineer Intern (Developer Infrastructure) - 2024 Summer (PhD)

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1mo ago

🚀 Summer Internship

San Jose

AI generated summary

  • Seeking PhD Software Engineer Intern with expertise in distributed computing, machine learning, programming languages (C/C++, Go, Python), and GPU-based high-performance computing. Familiarity with Tensorflow, Pytorch, MxNet, and Linux environment is necessary.
  • The Software Engineer Intern will focus on developing and deploying machine learning systems, including task scheduling and system management, to improve machine learning services for customers at ByteDance. They will iterate and improve the system based on customer-driven scenarios to enhance overall performance.

Summer Internship

Software EngineeringSan Jose


  • We are looking for talented individuals to join us for an internship in 2024. Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at ByteDance.
  • Internships at TikTok 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 12-24 weeks beginning in May/June 2024. 


  • Master distributed, parallel computing principles; know the recent advances in computing, storage, networking, and hardware technologies;
  • Familiar with state-of-the-art machine learning algorithms and mainstream platforms (e.g., Tensorflow, Pytorch, MxNet);
  • Master at least one or two programming languages in a Linux environment such as C/C++, Go, Python, etc;
  • Experience in GPU based high-performance computing is a plus

Education requirements


Area of Responsibilities

Software Engineering


  • Development of machine learning systems, including key computing development, task scheduling, and machine learning system management and operation
  • Deployment of machine learning services
  • Online serving of machine learning models
  • Iterate and develop the system using customer-driven scenarios


Work type

Full time

Work mode



San Jose