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职位TikTok

Machine Learning Engineer Intern (TikTok Shop Global E-Commerce, Recommendation Alliance) - 2026 Start (BS/MS)

TikTok

Machine Learning Engineer Intern (TikTok Shop Global E-Commerce, Recommendation Alliance) - 2026 Start (BS/MS)

TikTok

Singapore

·

On-site

·

Full-time

·

2mo ago

福利待遇

Healthcare

Equity

Parental Leave

必备技能

Python

TensorFlow

PyTorch

Machine Learning Engineer Intern (Tik Tok Shop Global E-Commerce, Recommendation Alliance) - 2026 Start (BS/MS)

3+ months ago• Singapore
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

Responsibilities:

Team Introduction
The alliance team aims to serve merchants and creators on the e-commerce platform to meet merchants' business indicators and improve creators' creative efficiency. By cooperating with merchants and creators, we aim to provide high-quality content and a personalized shopping experience for Tik Tok users, create efficient shopping tools at seller centers, and promote cooperation between merchants and creators.

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. Watch your ambitions become reality as your inspiration brings infinite opportunities at Tik Tok.

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 Tik Tok and its affiliates' jobs globally.

Applications will be reviewed on a rolling basis - we encourage you to apply early.

Successful candidates must be able to commit to at least 3 months long internship period.

Responsibilities:

  • Build and design large-scale machine learning algorithms to model the real-time interests of creators to improve conversion efficiency.
  • Optimize Tik Tok's massive commodity relationship mining and ranking and recall of creators' product recommendations, and improve the overall GMV of the platform.
  • Use the large scale of data to deeply analyze the behavior of creators and merchants and build targeted algorithm strategies to empower creators and merchants, improve merchants' monetization efficiency, and boost industrial upgrading.
  • Support the rapid development of Tik Tok's e-commerce business, serve millions of merchants, explore more efficient business models, satisfy users with the best shopping experience, and promote ecological development.
  • Support the production of scalable and optimised AI/machine learning (ML) models.
  • Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models.

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Qualifications:

  • Minimum Qualifications

  • Undergraduate or Postgraduate currently pursuing a Degree/Master in Software Development, Computer Science, Computer Engineering, or a related technical discipline.

  • Solid theoretical understanding of machine learning, with familiarity with algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, and Deep Neural Networks.

  • Experience in training and deploying models using frameworks like Py Torch, Tensor Flow, or MXNet.

  • Strong learning ability, with excellent communication and teamwork skills.

  • Preferred Qualifications

  • Publications at conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI, Rec Sys, and similar.

  • Practical Experience: Experience from internships, research, or projects, especially in fields like e-commerce, recommendations, or search engines.

  • Problem Solving and Creativity: Passionate about technology and solving challenging problems, with high levels of creativity and quick problem-solving capabilities.

By submitting an application for this role, you accept and agree to our global applicant If you have any questions, please reach out to us at apac-earlycareers@tiktok.com

Client-provided location(s): Singapore

Job ID: Tik Tok-7532122879539251474

Employment Type: INTERN

Posted: 2025-07-29T01:28:02
Apply 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

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关于TikTok

TikTok

TikTok

Late Stage

A short-form video entertainment app and social network platform

10,001+

员工数

Los Angeles

总部位置

$220B

企业估值

评价

3.8

10条评价

工作生活平衡

2.8

薪酬

3.7

企业文化

4.1

职业发展

3.2

管理层

2.9

68%

推荐给朋友

优点

Great team dynamics and support

Innovative and creative culture

Good learning opportunities

缺点

Work-life balance challenges

Fast-paced and stressful environment

High expectations and tight deadlines

薪资范围

49个数据点

Mid/L4

Senior/L5

Mid/L4 · Applied AI Product Data Scientist

1份报告

$273,000

年薪总额

基本工资

$210,000

股票

-

奖金

-

$273,000

$273,000

面试经验

2次面试

难度

4.0

/ 5

时长

21-35周

体验

正面 0%

中性 0%

负面 100%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Behavioral Interview

5

Final Round

6

Offer

常见问题

Coding/Algorithm

Behavioral/STAR

Technical Knowledge

Culture Fit