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Machine Learning Engineer Intern (Monetization Technology-Vertical Business Technology) - 2024 Start (BS/MS/PhD) - San Jose

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1mo ago

πŸš€ Summer Internship

San Jose

AI generated summary

  • Seeking a candidate pursuing a degree in Computer Science, Mathematics, or a related field with 2+ years of research or machine learning modeling experience. Must have strong programming skills in C/C++ and Python, knowledge in statistics, and theoretical understanding of deep learning concepts. Familiarity with machine learning frameworks such as TensorFlow/Pytorch/MXNet is required, with preferences for candidates focused on statistical learning or expertise in Factorization Machine, Uplift Modeling, Diffusion Models, or Reinforcement Learning.
  • The Machine Learning Engineer Intern will be working on building scalable ML systems for improving ads ranking, experimenting with new features for better accuracy, understanding platform objectives, and developing core systems and algorithms for ad quality and relevancy.

Summer Internship

Dataβ€’San 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 TikTok..
  • 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.


  • Currently pursuing an Bachelor's/Master's Degree in Computer Science, Mathematics, Statistics, or a related technical discipline with 2+ years research or machine learning modeling experience.
  • - Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.
  • Good analytical thinking capability. Essential knowledge and skills in statistics.
  • Good theoretical grounding in deep learning concepts and techniques.
  • Familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/Pytorch/MXNet), familiar with its architecture and implementation mechanism.
  • Preferred Qualifications:
  • PhD candidate focused on a statistical learning related field.
  • Good knowledge in one of the following fields: Factorization Machine, Uplift Modeling, Diffusion Models, Reinforcement Learning.
  • Basic understanding of large recommendation system and ads serving system concepts.

Education requirements

Currently Studying

Area of Responsibilities



  • Build highly scalable machine learning systems/models to improve ads ranking results.
  • Explore, develop and experiment with new features to improve model accuracy.
  • Understand advertisement platform objectives and take full advantage of modern machine learning to improve ad quality, relevancy, and select the best ad formats delivered to end-users.
  • Develop robust core systems and algorithms, including ads format selection system, ads ranking system, model serving system, etc.


Work type

Full time

Work mode



San Jose