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TikTok
TikTok

Leading short-form video platform

Machine Learning Engineer - Core Feed Recommendation - Singapore

RoleMachine Learning
LevelMid Level
LocationSingapore
WorkOn-site
TypeFull-time
Posted3 months ago
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Benefits and perks

Parental Leave

Remote Work

Required skills

Apache Spark

TensorFlow

Airflow

Machine Learning Engineer

  • Core Feed Recommendation
  • Singapore

3+ months ago• Singapore
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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:

Tik Tok Core Feed Recommendation team sits in the center of Tik Tok, designs, implements and improves the core recommendation algorithm that powers the "for you" feed, "following" feed, etc. of the Tik Tok app. The recommendation system we built connects hundreds of millions of users with relevant content out of billions of videos in real-time, and inspires high-quality content creation for millions of creators on the platform.

The User Growth team is an essential pillar of the Core Feed Recommendation team, directly responsible for implementing and refining new user acquisition and retention strategies. Our team is committed to achieving Tik Tok's ultimate goals through developing high-performance models and sound strategies. We take pride in our rigorous approach to applied research, innovative system design, and steadfast pragmatism.

We are looking for strong research scientists and engineers at all levels, who are excited about growing their business understanding, building highly scalable and reliable software, and partnering across disciplines with global teams, in pursuit of excellence.

What you'll do:

  • Implement machine learning algorithms at large scales to optimize and improve new user acquisition efficiency, and leverage acquisition signals to improve new user retention across all ranking phases including but not limited to retrieval, ranking, re-ranking and etc.

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  • Work cross functionally with product managers, data scientists and product engineers to understand insights, formulate problems, design and refine machine learning algorithms, and communicate results to peers and leaders.
  • Run regular A/B tests, perform analysis and iterate algorithms accordingly.
  • Have a good understanding of end-to-end machine learning systems. Work with infra teams on improving efficiency and stability.

Qualifications:

  • Minimum Qualifications
  • Hands-on experience in one or more of the areas: recommender systems, machine learning, deep learning, pattern recognition, data mining, computer vision, NLP, causal inference, content understanding or multimodal machine learning
  • Strong programming skills in Python and/or C/C++, and a deep understanding of data structures and algorithms
  • Familiar with architecture and implementation of at least one mainstream machine learning programming framework (Tensor Flow/Pytorch/MXNet)
  • Good communication and teamwork skills, be passionate about learning new techniques and taking on challenging problems
  • Prior industry experience with main components of recommendation systems(retrieval, ranking, re-ranking, cold-start etc.) is a plus but not required

Preferred Qualifications:

  1. Publications at main conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI, Rec Sys or related conferences
  2. Strong tracking record of success in data mining, machine learning, or ACM-ICPC/NOI/IOI competitions
  3. Participation in public/open-source AI-related projects which are of high visibility
    4.3 years relevant work experience from a large-scale internet business

Client-provided location(s): Singapore

Job ID: Tik Tok-7520494692112353543

Employment Type: OTHER

Posted: 2025-06-29T00:25:23
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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)

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About TikTok

TikTok

TikTok

Late Stage

While TikTok remains accessible to civilians in most countries and regions, a minority — including India, Iran, China, and Afghanistan — have imposed nationwide bans. In the United States, legislation providing for a full ban was enacted but not implemented because of a restructure of U.S.

10,001+

Employees

Los Angeles

Headquarters

$220B

Valuation

Reviews

10 reviews

3.8

10 reviews

Work-life balance

2.8

Compensation

4.0

Culture

4.2

Career

3.5

Management

2.5

72%

Recommend to a friend

Pros

Great team dynamics and support

Innovative and creative culture

Good learning opportunities

Cons

Poor work-life balance and long hours

High stress and overwhelming workload

Management and leadership issues

Salary Ranges

58 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · ANTI-FRAUD DATA ANALYST - USDS

1 reports

$143,750

total per year

Base

$125,000

Stock

-

Bonus

-

$143,750

$143,750

Interview experience

2 interviews

Difficulty

4.0

/ 5

Duration

21-35 weeks

Experience

Positive 0%

Neutral 0%

Negative 100%

Interview process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Behavioral Interview

5

Final Round

6

Offer

Common questions

Coding/Algorithm

Behavioral/STAR

Technical Knowledge

Culture Fit