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(General Hire) Machine Learning Scientist Intern (TikTok Recommendation - TikTok-Data) - 2025 Summer/Fall (PhD)

AT TikTok
TikTok

(General Hire) Machine Learning Scientist Intern (TikTok Recommendation - TikTok-Data) - 2025 Summer/Fall (PhD)

San Jose, CA

Responsibilities

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us
Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.

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At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.

Powered by world-class machine learning technology, the TikTok Live Recommendation Team aims at providing the best livestream watching experience on the platform. We build algorithms to recommend the most relevant livestreams to users and help to grow a wholesome livestream content ecosystem.

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.

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.

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 12-24 weeks and begins in May/June 2025 or August/September 2025. Successful candidates must be able to commit to one of the following start dates below:

(Select below options for Summer)
- Monday, May 12
- Monday, May 19
- Tuesday May 27 (Memorial Day May 27)
- Monday, June 9
- Monday, June 23

(Select below options for Fall)
- Monday, August 11
- Monday, August 25
- Monday, September 8
- Monday, September 22
Please state your availability clearly in your resume (Start date, End date).

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.

Responsibilities:
1. Build industry-leading recommendation system, improving user experience, content ecosystem and platform security;
2. Deliver end-to-end machine learning solution to address critical product challenges;
3. Own the full stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance;
4. Work with cross functional teams to design product strategies and build solutions to grow TikTok in important markets.

Qualifications

Minimum Qualifications:
1. Currently pursuing a PhD with a background in computer science, machine learning, or similar fields;
2. Good knowledge of theoretical and empirical research in addressing research problems;
3. Solid knowledge and experience with at least one popular deep learning framework (e.g., PyTorch,TensorFlow) and familiarity with deep neural network architectures.

Preferred Qualifications:
1. Research experience in one or more of the following fields: applied machine learning, machine learning infrastructure, large-scale recommendation system, market-facing machine learning product;
2. Strong first-author publications record in top AI conferences or journals(e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL etc.);
3. Proficient in C/C++, Python, and shell programming languages, and have a deep understanding of data structure and algorithm design;
4. Internship experience in an AI research organization.

General Hire: If you see the "general hire" in the title of this position, it means that the position is for multiple departments. After applying for this role, your profile will be considered for multiple openings across the department; team-matching will be conducted by hiring team based on your resume.
The department this position is considered for include but not limited to:Data-Live, Data-Plus, and Data-Responsible Recommendation System.

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://shorturl.at/cdpT2.

Client-provided location(s): San Jose, CA, USA
Job ID: TikTok-7400657277185181989
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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