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Machine Learning Engineer, Access Safety - TikTok BRIC - Singapore

TikTok

Machine Learning Engineer, Access Safety - TikTok BRIC - Singapore

TikTok

Singapore

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Flexible PTO policy

Remote work flexibility

Annual team offsites

Wellness benefits

Required Skills

Apache Spark

Python

Airflow

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Tik Tok

Machine Learning Engineer, Access Safety

  • Tik Tok BRIC - Singapore

3+ months ago• Singapore
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:

The Tik Tok-BRIC-Access Safety team is missioned to protect the Tik Tok platform and users from malicious automation, fake traffic, and compromised devices. We ensure all inbound traffic and device identities remain authentic and abuse-resistant.

In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives. You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolution of a phenomenal product eco-system.

  • Perform access-risk detection and analysis using ML models and rule logic.
  • Develop device authenticity labels.
  • Execute real-time enforcement (block / throttle / challenge) and broader punishment mechanisms.
  • Deliver signals, metrics, and dashboards to partner teams.
  • Perform access-risk detection and analysis using ML models and rule logic.
  • Develop device authenticity labels.
  • Execute real-time enforcement (block / throttle / challenge) and broader punishment mechanisms.
  • Deliver signals, metrics, and dashboards to partner teams.

Qualifications:

  • Minimum Qualifications

  • Experience in safety, security, or risk control or related domains.

  • Bachelor or above degree in computer science, statistics, or other relevant, machine-learning-heavy majors.

  • Strong machine learning background. Proficiency or publications in modern machine learning theories and applications such as deep neural nets, transfer/multi-task learning, reinforcement learning, time series or graph unsupervised learning.

  • Preferred Qualifications

  • Experience in building detection and defence for Bot/large abusive traffic.

  • Solid communication and collaboration skills with the ability to work effectively with internal teams in a cross-functional environment

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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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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