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Machine Learning Scientist Intern (TikTok-Recommendation) - 2026 Start (PhD)

TikTok

Machine Learning Scientist Intern (TikTok-Recommendation) - 2026 Start (PhD)

TikTok

San Jose, CA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Annual team offsites

Learning and development stipend

Top Tier compensation with equity

Parental leave program

Health, dental, and vision coverage

Flexible PTO policy

Required Skills

Python

SQL

TensorFlow

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Tik Tok

Machine Learning Scientist Intern (Tik Tok-Recommendation) - 2026 Start (PhD)

3+ months ago• San Jose, CA
Viewed on February 1, 2026
Apply on company site

About Us

Tik Tok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.

  • Size: 5001-10000 employees
  • Industry: Entertainment & Gaming, Social Media, Technology

View Company Profile:

Responsibilities:

About the Team:

Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven.

We are looking for talented individuals to join us for an internship in 2026. Internships at Tik Tok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at Tik Tok.

Internships at Tik Tok 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.

In this role, you'll have the opportunity to:

  • Drive the development of industry-leading recommendation systems that elevate user experience, strengthen platform safety, and empower a vibrant content ecosystem.
  • Deliver impactful, end-to-end machine learning solutions that tackle high-priority product challenges related to content understanding, LLMs, robustness, and fairness.
  • Own and optimize the full-stack ML pipeline-from algorithm design to system infrastructure-to continuously push the boundaries of recommendation performance.
  • Collaborate with cross-functional teams to craft innovative product strategies and develop intelligent solutions that fuel Tik Tok's growth in key global markets.

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By signing up, you agree to our Qualifications

Minimum Qualifications:

  • Currently pursuing a PhD with a background in computer science, machine learning, or similar fields;
  • Good knowledge of theoretical and empirical research in addressing research problems;
  • Solid knowledge and experience with at least one popular deep learning framework (e.g., Py Torch,Tensor Flow) and familiarity with deep neural network architectures.

Preferred Qualifications:

  • 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;
  • Strong first-author publications record in top AI conferences or journals(e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL etc.);
  • Proficient in C/C++, Python, and shell programming languages, and have a deep understanding of data structure and algorithm design;
  • Internship experience in an AI research organization.

Client-provided location(s): San Jose, CAJob ID: Tik Tok-7519241729582516487Employment Type: INTERNPosted: 2025-06-27T00:27:05Apply on company site

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

Hear directly from employees about what it is like to work at Tik Tok.
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Next Up Tik Tok Client Provided Video 101:20

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  • 02:18Working at Tik Tok- Get Ready With Ali01:20Tik Tok Client Provided Video 100:33Client Provided Video 2 - Tik Tok02:07Working at Tik Tok
  • Limitless Possibilities01:41Working at Tik Tok
  • Women's Community01:31Working at Tik Tok
  • Women's Empowerment01:45Working At Tik Tok
  • BLXCK01:27Working at Tik Tok
  • Diversity, Equity and Inclusion with BLXCK
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About TikTok

TikTok

TikTok

Late Stage

A short-form video entertainment app and social network platform

10,001+

Employees

Los Angeles

Headquarters

$220B

Valuation

Reviews

3.1

3 reviews

Work Life Balance

1.5

Compensation

2.0

Culture

1.2

Career

1.8

Management

1.0

5%

Recommend to a Friend

Pros

Limited positive feedback available

Company size allows for potential opportunities

Technology platform experience

Cons

Mass layoffs and poor handling of terminations

Unprofessional management and HR behavior

Exposure to traumatic content without adequate support

Salary Ranges

52 data points

Mid/L4

Senior/L5

Mid/L4 · Applied AI Product Data Scientist

1 reports

$273,000

total / year

Base

$210,000

Stock

-

Bonus

-

$273,000

$273,000

Interview Experience

4 interviews

Difficulty

3.5

/ 5

Duration

21-35 weeks

Experience

Positive 0%

Neutral 25%

Negative 75%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Interviews

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Data Structures