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Machine Learning Engineer Intern (E-commerce-Recommendation) - 2025 Summer/Fall (PhD)

AT TikTok
TikTok

Machine Learning Engineer Intern (E-commerce-Recommendation) - 2025 Summer/Fall (PhD)

San Jose, CA

Responsibilities

Our E-commerce Recommendation Team is responsible for building up and scaling our recommendation system to provide the best shopping experience for our TikTok users. We are looking for talented individuals to join our team in 2024. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.
We are looking for talented individuals to join our team in 2024. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.

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We are looking for talented individuals to join us for an internship in 2025. 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. It runs for 12 weeks beginning in May/June 2025 or August/September 2025 (Select May if Summer or August if Fall
Please state your availability clearly in your resume (Start date, End date).

Summer Start Dates:
Monday, May 12
Monday, May 19
Tuesday May 27 (Memorial Day May 26)
Monday, June 9
Monday, June 23

Fall Start Dates:
Monday, August 11
Monday, August 25
Monday, September 8
Monday, September 22

Applications will be reviewed on a rolling basis. We encourage you to apply early. Candidates can apply to a maximum of TWO positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally.

Candidates who pass resume evaluation will be invited to participate in TikTok's technical online assessment through HackerRank.

Responsibilities:
- Work in a team to conduct cutting-edge research in machine learning algorithms, such as retrieval and recommendation algorithms;
- Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in TikTok;
- Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently;
- Apply machine learning algorithms to improve the different business scenarios, such as search ranking, natural language and video understanding, and trust and safety.

Qualifications

Minimum Qualifications:
- Currently pursuing PhD in Computer Science, related technical field or equivalent industrial research experience;
- Experience in one of the following fields: recommendation systems, online advertising, information retrieval, natural language processing, computer vision, machine learning, large-scale data mining, or related fields preferred;
- Familiar with at least one of the mainstream deep learning frameworks, such as TensorFlow or PyTorch;
- Passionate about solving complex and challenging problems;
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Client-provided location(s): San Jose, CA, USA
Job ID: TikTok-7488085993833613575
Employment Type: Intern

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Dental Insurance
    • Vision Insurance
    • HSA
    • Life Insurance
    • Fitness Subsidies
    • Short-Term Disability
    • Long-Term Disability
    • On-Site Gym
    • Mental Health Benefits
    • Virtual Fitness Classes
  • Parental Benefits

    • Fertility Benefits
    • Adoption Assistance Program
    • Family Support Resources
  • Work Flexibility

    • Flexible Work Hours
    • Hybrid Work Opportunities
  • Office Life and Perks

    • Casual Dress
    • Snacks
    • Pet-friendly Office
    • Happy Hours
    • Some Meals Provided
    • Company Outings
    • On-Site Cafeteria
    • Holiday Events
  • Vacation and Time Off

    • Paid Vacation
    • Paid Holidays
    • Personal/Sick Days
    • Leave of Absence
  • Financial and Retirement

    • 401(K) With Company Matching
    • Performance Bonus
    • Company Equity
  • Professional Development

    • Promote From Within
    • Access to Online Courses
    • Leadership Training Program
    • Associate or Rotational Training Program
    • Mentor Program
  • Diversity and Inclusion

    • Diversity, Equity, and Inclusion Program
    • Employee Resource Groups (ERG)

Company Videos

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