Technology
Lead Machine Learning Engineer - Video Recommendation-Content Ecosystem - Singapore
Location
:
Singapore
Employment Type
:
Regular
Job Code
:
A28226
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

Job Information
About TikTok
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok’s global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
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Why Join Us
Inspiring creativity is at the core of TikTok’s mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
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We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We’re resilient and embrace challenges as they come. By constantly iterating and fostering an “Always Day 1” mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
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Diversity & Inclusion
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TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too

Please refer the Job description for details