Machine Learning Engineer - Feed E-Commerce - Singapore

About Us Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.​ Why Join ByteDance Inspiring creativity is at the core of ByteDance's mission. Our innovative products are 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 enrich life - a mission we work towards every day.​ As ByteDancers, 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. 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.​ Diversity & Inclusion​ ByteDance 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 ByteDance, our mission is to inspire creativity and enrich life. 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.​ Job highlights Yoga and fitness, Five insurances and one fund, Career growth opportunity, Paid leave, Flat organization, 100+ mil users, Industry experts, Meals provided, Competitive compensation Responsibilities About the Team We Are the E-commerce Short Video & Live Recommendation Team. As pioneers reshaping global shopping experiences, we specialize in end-to-end optimization of short video recommendation systems across Europe, Southeast Asia, and Latin America. Our mission spans the full recommendation pipeline - from content supply, candidate retrieval, pre-ranking, ranking, blending to user experience refinement - building a culture-adaptive recommendation engine for our diverse markets. Breaking through traditional "product shelf" e-commerce paradigms, we reinvent recommendation systems for the short video era. Our team combines academic excellence from top global universities with industrial expertise in billion-DAU recommendation systems. By leveraging cutting-edge machine learning technologies, we create dynamic intelligent matching bridges between massive product catalogs and global users. We are committed to providing a personalized, proactive, and efficient consumption experience for users through live-stream e-commerce content by connecting them with exceptional sellers and high-quality products. Our team is responsible for developing innovative recommendation algorithms and techniques to enhance user engagement and satisfaction, effectively transforming creative ideas into business-impacting solutions. Responsibilities: - Design and apply machine learning algorithm and recommendation strategies to improve users' experience on e-commerce content, including videos and livestreams. - Understand ecosystem of e-commerce content and use algorithm and strategy to make it thrive. - Work with product and ops team to deliver features that drives growth of e-commerce content on our platform. - Build industry leading recommendation system; develop highly scalable classifiers and tools leveraging machine learning Qualifications Minimum Qualifications 1. Bachelor's degree in computer science or a related technical discipline, with at least 2 years of related work experience; 2. Solid experience with data structures and algorithms; 3. Software development experience through hands on coding in a general purpose programming language; 4. Experience in one or more of the following areas: machine learning, recommendation systems, data mining or other related areas; 5. Strong communication and teamwork skills; 6. Passion about technologies and solving challenging problems. Preferred Qualification: Preferred to have more than 3 years experience in the recommendation algorithm domain.