refresh

トレンド企業

Trending

採用

JobsTikTok

Machine Learning Engineer, Core Feed Recommendation - Singapore

TikTok

Machine Learning Engineer, Core Feed Recommendation - Singapore

TikTok

Singapore

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Parental leave program

Remote work flexibility

Learning and development stipend

Flexible PTO policy

Required Skills

Airflow

TensorFlow

SQL

Machine Learning Engineer, Core Feed Recommendation

  • Singapore

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:

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.

Want more jobs like this?

Get

Data and Analytics jobs in

Singapore delivered to your inbox every week.

Email Address

Send me The Muse newsletters for the best in career advice and job search tips.

Get jobs!
By signing up, you agree to our & .

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.
  • 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

Client-provided location(s): Singapore

Job ID: Tik Tok-7263405519716714811

Employment Type: OTHER

Posted: 2025-01-21T00:51:25
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

Hear directly from employees about what it is like to work at Tik Tok.

Apply on company site

Similar Jobs

Suggested Searches

Data and Analytics jobsmid jobsTikTok jobsAll jobs

Search Additional Jobs

Machine Learning Engineer Jobs in SingaporeJobs in SingaporeData and Analytics JobsData and Analytics Jobs in Singapore

of Use](https://www.themuse.com/user/Popular Jobs

Get Involved

Join The Conversation:

Total Views

0

Apply Clicks

0

Mock Applicants

0

Scraps

0

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