Staff Software Engineer, Machine Learning

About the Team Seoul Studios is Tinder's Seoul-based product studio, chartered to build breakthrough innovations in how people meet and connect. We move fast — incubating new, interactive dating experiences, running rapid experiments, and shipping features that raise engagement and improve reconsideration for members around the world. Based in Seoul, the pod is a self-contained, cross-functional team of iOS, Android, web, and backend engineers working shoulder to shoulder with Product, Design, and Data, and partnering with teams across Seoul and our U.S. headquarters to take ideas from early experiment to global scale. Tinder is available in 160+ countries, but the experience is still largely one-size-fits-all — and that's the opportunity. International Growth exists to change it: to build organic growth flywheels through deep localization, in close partnership with Marketing, starting in core APAC cities and turning what works into a repeatable, scalable playbook we can take to new markets. Based in Seoul, we're a small, autonomous, cross-functional pod — Product, Design, Engineering, and Data working side by side, moving fast and shipping real experiments — in close partnership with regional local teams (Japan, India, and more) and the global organizations at our U.S. headquarters. Design sits at the center of the bet: making Tinder feel like it was built for each market, not merely translated for it. About the Team Seoul Studios is Tinder's Seoul-based product studio, chartered to build breakthrough innovations in how people meet and connect. We move fast — incubating new, interactive dating experiences, running rapid experiments, and shipping features that raise engagement and improve reconsideration for members around the world. Based in Seoul, the pod is a self-contained, cross-functional team of iOS, Android, web, and backend engineers working shoulder to shoulder with Product, Design, and Data, and partnering with teams across Seoul and our U.S. headquarters to take ideas from early experiment to global scale. Tinder is available in 160+ countries, but the experience is still largely one-size-fits-all — and that's the opportunity. International Growth exists to change it: to build organic growth flywheels through deep localization, in close partnership with Marketing, starting in core APAC cities and turning what works into a repeatable, scalable playbook we can take to new markets. Based in Seoul, we're a small, autonomous, cross-functional pod — Product, Design, Engineering, and Data working side by side, moving fast and shipping real experiments — in close partnership with regional local teams (Japan, India, and more) and the global organizations at our U.S. headquarters. Design sits at the center of the bet: making Tinder feel like it was built for each market, not merely translated for it. The Team The Engineering team is responsible for building innovative features and resilient systems that bring people together. We're always experimenting with new features to engage with our members. Although we are a high-scale tech company, the member-to-engineer ratio is very high—making the level of impact each engineer gets to have at Tinder enormous. Our ML team is responsible for developing machine learning algorithms and systems for Tinder recommendations. Recommendation algorithms directly determine potential matches on Tinder and optimize the entire ecosystem to drive critical business metrics. You'll have a unique opportunity to join a company with a global footprint while working on a team small enough for you to feel the impact each day. Where you'll work: This is a hybrid role and requires in-office collaboration three times per week. Our office is located in Seoul. Application Requirements English Resume #Tinder Application Requirements English Resume #Tinder In this role, you will: Lead the modeling efforts of Tinder’s recommendation system Apply state-of-the-art machine learning techniques, including deep learning, reinforcement learning, causal inference, and optimization, to enhance our foundational models. Develop algorithms that optimize our complex ecosystem to meet multiple disparate objectives. Lead the research and development of novel algorithms and models, staying at the forefront of advancements in ML technologies. Work with big data to improve the accuracy and relevance of recommendations. Collaborate with other machine learning engineers, backend software engineers, and product managers to integrate ML models into our systems, improving user experience and driving business objectives. Mentor and guide team members, fostering their growth and enabling them to reach their full potential. You’ll need: 8+ years of hands-on experience in machine learning, with a proven track record of delivering impactful solutions at scale. PhD or MS in machine learning, computer science, statistics, or another highly quantitative field. Hands-on experience in designing and building large-scale recommendation systems In-depth knowledge of deep neural networks, particularly in the recommendations Proficiency in deep learning frameworks such as PyTorch, TensorFlow, Keras, etc. Proficiency in Python, Java, Scala, or similar programming languages. Strong decision-making skills with a bias for action and the ability to navigate ambiguity with confidence. Proven leadership abilities to inspire and motivate teams to excel and achieve ambitious goals.