TikTok
Machine Learning Engineer, Core Feed Recommendation - Singapore
Job Location
Singapore, Singapore
Job Description
Overview Machine Learning Engineer, Core Feed Recommendation - Singapore 6 days ago Be among the first 25 applicants Get AI-powered advice on this job and more exclusive features. Responsibilities TikTok Core Feed Recommendation team sits in the center of TikTok, designs, implements and improves the core recommendation algorithm that powers the "for you" feed, "following" feed, etc. of the TikTok 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 TikTok'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. 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 Note: The original content uses bold for sections; this version preserves the text while using allowed tags. Minimum Qualifications include: Hands-on experience in one or more of the following 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 framework (TensorFlow/PyTorch/MXNet) Good communication and teamwork skills, and a passion for learning new techniques and tackling challenging problems Prior industry experience with main components of recommendation systems (retrieval, ranking, re-ranking, cold-start) is a plus but not required Preferred Qualifications : Publications at major conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI, RecSys or related conferences Strong track record in data mining, machine learning, or ACM-ICPC/NOI/IOI competitions Participation in public/open-source AI-related projects with high visibility About TikTok TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok\'s global headquarters are in Los Angeles and Singapore, with offices worldwide. Why Join Us Inspiring creativity is at the core of TikTok\'s mission. Our innovative product helps people authentically express themselves, discover and connect. We strive to do great things with great people, fostering curiosity, humility and impact in a rapidly growing tech company. We embrace challenges as opportunities to learn and innovate as one team. By constantly iterating and maintaining an "Always Day 1" mindset, we aim for meaningful breakthroughs for our company and users. Join us. Diversity & Inclusion TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people globally and our workplace reflects that diversity. We are passionate about celebrating diverse voices and creating an environment that reflects the communities we reach. Seniority level Associate Employment type Full-time Job function Engineering and Information Technology Industries Technology, Information and Internet Referrals increase your chances of interviewing at TikTok by 2x Location: Queenstown, Central Singapore Community Development Council, Singapore 8 months ago J-18808-Ljbffr
Location: Singapore, Singapore, SG
Posted Date: 10/15/2025
Location: Singapore, Singapore, SG
Posted Date: 10/15/2025
Contact Information
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