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Machine Learning Engineer Graduate (TikTok Shop Global E-Commerce, Risk Control) - 2026 Start (PhD)

TikTok

Machine Learning Engineer Graduate (TikTok Shop Global E-Commerce, Risk Control) - 2026 Start (PhD)

TikTok

Singapore

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Annual team offsites

Flexible PTO policy

Health, dental, and vision coverage

Parental leave program

Required Skills

Python

TensorFlow

PyTorch

Responsibilities

Team Introduction

The E-Commerce Risk Control (ECRC) team is missioned:

  • To protect Tiktok E-Commerce users, including and beyond buyer, seller, creator;
  • By securing the integrity of our ecommerce ecosystem and providing a safe shopping experience on the platform;
  • Through building infrastructures, platforms and technologies, as well as collaborating with many cross-functional teams and stakeholders.

In this team you'll have a unique and exciting opportunity to have first-hand exposure to build scalable and robust, intelligent and privacy-safe, secure and product-friendly systems via AI technology and data science products. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolvement of a phenomenal product eco-system.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at Tik Tok.

Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.

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.

Key Responsibilities

  • Develop machine learning solutions for identifying and preventing various fraudulent activities.
  • Analyze massive business and security data to mine abnormal user behavior, and uncover evolving risky patterns.
  • Build data pipeline to enable scalable and real-time risk prevention.
  • Analyze / test the effectiveness of the built solutions.
  • Work in a cross-functional team setting to mitigate business risks.
  • Work with relevant software platform to develop/deploy/monitor the models.

Qualifications

Minimum Qualifications

  • Final year or recent PhD graduate with a background in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
  • Good coding skills in one or more programming language.

Preferred Qualifications

  • Familiar with machine learning frameworks such as scikit-learn, tensorflow, pytorch.
  • Ability to think critically, rationally, and communicate in result-oriented, data-driven manner.

Additional Information

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

If you have any questions, please reach out to us at apac-earlycareers@tiktok.com

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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