Lead Machine Learning Engineer - Video Recommendation-Content Ecosystem - Singapore
Sep 6, 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
About the Team
TikTok content ecosystem team, responsible for designing and optimizing TikTok information delivery and author growth mechanisms to ensure the healthy and sustainable development of the TikTok community. Our work involves optimizing large-scale recommendation algorithms, solving optimization problems with complex constraints, designing and implementing recommendation architectures for various scenarios, and conducting complex and in-depth analysis of product data. Here, you can delve into the improvement and optimization of Machine Learning algorithms, explore cutting-edge technologies; apply algorithms to business through in-depth understanding and thinking of products; and influence the future development direction of products through in-depth analysis of product and content ecology.
Responsibilities
1. Design and develop TikTok's social recommendation algorithms, building an industry-leading recommendation system to deliver a world-class user experience.
2. Integrate machine learning techniques with various business scenarios (content consumption, social interaction, notifications, following, etc.) to optimize models and strategies, continuously improving recommendation performance.
3. Collaborate closely with product and operations teams to deeply understand user and creator behaviors, and develop targeted algorithm strategies to foster a healthy ecosystem.
4. Research next-generation social recommendation models based on Graph Neural Networks (GNNs) and full-lifecycle user sequence modeling.
Qualifications
Minimum Qualifications
- Bachelor's degree (or more) in computer science or a related technical discipline
- Experienced in leading projects and collaborating with teams across different timezones;
- Solid experience with data structures or algorithms;
- 2 years and above recommendation system/machine learning/data mining experience from a large-scale social-media business
- Software development experience through hands on coding in a general purpose programming language
- Familiar with the training and deployment of one or more framework models of Tensorflow/Pytorch/MXNet.
- Strong communication and teamwork skills
- Excellent business sense, passion about technologies and solving challenging problems
About the Team
TikTok content ecosystem team, responsible for designing and optimizing TikTok information delivery and author growth mechanisms to ensure the healthy and sustainable development of the TikTok community. Our work involves optimizing large-scale recommendation algorithms, solving optimization problems with complex constraints, designing and implementing recommendation architectures for various scenarios, and conducting complex and in-depth analysis of product data. Here, you can delve into the improvement and optimization of Machine Learning algorithms, explore cutting-edge technologies; apply algorithms to business through in-depth understanding and thinking of products; and influence the future development direction of products through in-depth analysis of product and content ecology.
Responsibilities
1. Design and develop TikTok's social recommendation algorithms, building an industry-leading recommendation system to deliver a world-class user experience.
2. Integrate machine learning techniques with various business scenarios (content consumption, social interaction, notifications, following, etc.) to optimize models and strategies, continuously improving recommendation performance.
3. Collaborate closely with product and operations teams to deeply understand user and creator behaviors, and develop targeted algorithm strategies to foster a healthy ecosystem.
4. Research next-generation social recommendation models based on Graph Neural Networks (GNNs) and full-lifecycle user sequence modeling.
Minimum Qualifications
- Bachelor's degree (or more) in computer science or a related technical discipline
- Experienced in leading projects and collaborating with teams across different timezones;
- Solid experience with data structures or algorithms;
- 2 years and above recommendation system/machine learning/data mining experience from a large-scale social-media business
- Software development experience through hands on coding in a general purpose programming language
- Familiar with the training and deployment of one or more framework models of Tensorflow/Pytorch/MXNet.
- Strong communication and teamwork skills
- Excellent business sense, passion about technologies and solving challenging problems
About the Team
TikTok content ecosystem team, responsible for designing and optimizing TikTok information delivery and author growth mechanisms to ensure the healthy and sustainable development of the TikTok community. Our work involves optimizing large-scale recommendation algorithms, solving optimization problems with complex constraints, designing and implementing recommendation architectures for various scenarios, and conducting complex and in-depth analysis of product data. Here, you can delve into the improvement and optimization of Machine Learning algorithms, explore cutting-edge technologies; apply algorithms to business through in-depth understanding and thinking of products; and influence the future development direction of products through in-depth analysis of product and content ecology.
Responsibilities
1. Design and develop TikTok's social recommendation algorithms, building an industry-leading recommendation system to deliver a world-class user experience.
2. Integrate machine learning techniques with various business scenarios (content consumption, social interaction, notifications, following, etc.) to optimize models and strategies, continuously improving recommendation performance.
3. Collaborate closely with product and operations teams to deeply understand user and creator behaviors, and develop targeted algorithm strategies to foster a healthy ecosystem.
4. Research next-generation social recommendation models based on Graph Neural Networks (GNNs) and full-lifecycle user sequence modeling.
Qualifications
Minimum Qualifications
- Bachelor's degree (or more) in computer science or a related technical discipline
- Experienced in leading projects and collaborating with teams across different timezones;
- Solid experience with data structures or algorithms;
- 2 years and above recommendation system/machine learning/data mining experience from a large-scale social-media business
- Software development experience through hands on coding in a general purpose programming language
- Familiar with the training and deployment of one or more framework models of Tensorflow/Pytorch/MXNet.
- Strong communication and teamwork skills
- Excellent business sense, passion about technologies and solving challenging problems
Responsibilities
ResponsibilitiesAbout the Team
TikTok content ecosystem team, responsible for designing and optimizing TikTok information delivery and author growth mechanisms to ensure the healthy and sustainable development of the TikTok community. Our work involves optimizing large-scale recommendation algorithms, solving optimization problems with complex constraints, designing and implementing recommendation architectures for various scenarios, and conducting complex and in-depth analysis of product data. Here, you can delve into the improvement and optimization of Machine Learning algorithms, explore cutting-edge technologies; apply algorithms to business through in-depth understanding and thinking of products; and influence the future development direction of products through in-depth analysis of product and content ecology.
Responsibilities
1. Design and develop TikTok's social recommendation algorithms, building an industry-leading recommendation system to deliver a world-class user experience.
2. Integrate machine learning techniques with various business scenarios (content consumption, social interaction, notifications, following, etc.) to optimize models and strategies, continuously improving recommendation performance.
3. Collaborate closely with product and operations teams to deeply understand user and creator behaviors, and develop targeted algorithm strategies to foster a healthy ecosystem.
4. Research next-generation social recommendation models based on Graph Neural Networks (GNNs) and full-lifecycle user sequence modeling.
Qualifications
QualificationsMinimum Qualifications
- Bachelor's degree (or more) in computer science or a related technical discipline
- Experienced in leading projects and collaborating with teams across different timezones;
- Solid experience with data structures or algorithms;
- 2 years and above recommendation system/machine learning/data mining experience from a large-scale social-media business
- Software development experience through hands on coding in a general purpose programming language
- Familiar with the training and deployment of one or more framework models of Tensorflow/Pytorch/MXNet.
- Strong communication and teamwork skills
- Excellent business sense, passion about technologies and solving challenging problems
Additional Information
- Posted: Sep 6, 2025