Machine Learning Engineer, Video Recommendation - Singapore
Jun 27, 2025 Singapore
About us
TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
- Size: 10,000+ employees
- Industry: Technology: Consumer Internet
Why you should apply for a job to TikTok:
4.5/5 in overall job satisfaction
4.5/5 in supportive management
100% say women are treated fairly and equally to men
100% would recommend this company to other women
100% say the CEO supports gender diversity
Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›
Responsibilities
TikTok-Data Video Recommendation Team is responsible for the personalized recommendation algorithms for TikTok's hundreds of millions of global users. Here, you will collaborate with top algorithm engineers in the industry, leveraging your expertise in deep learning, recommendation algorithms, and large models to continuously transform and enhance the TikTok user experience and content ecosystem.
Responsibility
1. Build industry leading recommendation system, develop highly scalable classifiers and tools leveraging machine learning
2. Understand product objectives and machine learning techniques, improve model and recommendation strategy
3. Understand user behavior and apply Machine Learning algorithms to optimize push notification and production experience
4. Work with TikTok cross functional teams to grow TikTok in important regional markets
Qualifications
Minimum Qualifications:
- Bachelor's degree (or more) in computer science or a related technical discipline
-Solid experience with data structures or algorithms
-Software development experience through hands on coding in a general purpose programming language
-Experience in one or more of the following areas: machine learning, recommendation systems, data mining or other related areas
-Strong communication and teamwork skills
-Passion about technologies and solving challenging problems
TikTok-Data Video Recommendation Team is responsible for the personalized recommendation algorithms for TikTok's hundreds of millions of global users. Here, you will collaborate with top algorithm engineers in the industry, leveraging your expertise in deep learning, recommendation algorithms, and large models to continuously transform and enhance the TikTok user experience and content ecosystem.
Responsibility
1. Build industry leading recommendation system, develop highly scalable classifiers and tools leveraging machine learning
2. Understand product objectives and machine learning techniques, improve model and recommendation strategy
3. Understand user behavior and apply Machine Learning algorithms to optimize push notification and production experience
4. Work with TikTok cross functional teams to grow TikTok in important regional markets
Minimum Qualifications:
- Bachelor's degree (or more) in computer science or a related technical discipline
-Solid experience with data structures or algorithms
-Software development experience through hands on coding in a general purpose programming language
-Experience in one or more of the following areas: machine learning, recommendation systems, data mining or other related areas
-Strong communication and teamwork skills
-Passion about technologies and solving challenging problems
TikTok-Data Video Recommendation Team is responsible for the personalized recommendation algorithms for TikTok's hundreds of millions of global users. Here, you will collaborate with top algorithm engineers in the industry, leveraging your expertise in deep learning, recommendation algorithms, and large models to continuously transform and enhance the TikTok user experience and content ecosystem.
Responsibility
1. Build industry leading recommendation system, develop highly scalable classifiers and tools leveraging machine learning
2. Understand product objectives and machine learning techniques, improve model and recommendation strategy
3. Understand user behavior and apply Machine Learning algorithms to optimize push notification and production experience
4. Work with TikTok cross functional teams to grow TikTok in important regional markets
Qualifications
Minimum Qualifications:
- Bachelor's degree (or more) in computer science or a related technical discipline
-Solid experience with data structures or algorithms
-Software development experience through hands on coding in a general purpose programming language
-Experience in one or more of the following areas: machine learning, recommendation systems, data mining or other related areas
-Strong communication and teamwork skills
-Passion about technologies and solving challenging problems
Responsibilities
ResponsibilitiesTikTok-Data Video Recommendation Team is responsible for the personalized recommendation algorithms for TikTok's hundreds of millions of global users. Here, you will collaborate with top algorithm engineers in the industry, leveraging your expertise in deep learning, recommendation algorithms, and large models to continuously transform and enhance the TikTok user experience and content ecosystem.
Responsibility
1. Build industry leading recommendation system, develop highly scalable classifiers and tools leveraging machine learning
2. Understand product objectives and machine learning techniques, improve model and recommendation strategy
3. Understand user behavior and apply Machine Learning algorithms to optimize push notification and production experience
4. Work with TikTok cross functional teams to grow TikTok in important regional markets
Qualifications
QualificationsMinimum Qualifications:
- Bachelor's degree (or more) in computer science or a related technical discipline
-Solid experience with data structures or algorithms
-Software development experience through hands on coding in a general purpose programming language
-Experience in one or more of the following areas: machine learning, recommendation systems, data mining or other related areas
-Strong communication and teamwork skills
-Passion about technologies and solving challenging problems
Additional Information
- Posted: Jun 27, 2025