Algorithm Engineer - Global Payment

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, Positive team atmosphere, Career growth opportunity 1. Provide algorithmic support for the growth of financial businesses under International Payments, including Payments, Credit Purchase, Credit Loans, and Treasury/Funds.Apply cutting-edge algorithmic techniques — causal inference, time-series learning, graph learning, reinforcement learning, weak supervision, and operations research/optimization — across scenarios such as marketing sensitivity modeling, financial time-series forecasting, financial relational learning, fund networks, sequential marketing, and cost/channel allocation optimization. Drive business growth through technical iteration and build an industry-leading intelligent growth algorithm team and capability. 2. Deploy algorithmic applications in commercialization scenarios such as marketing, recommendation, and advertising, broadening your algorithmic expertise and enhancing career competitiveness. Explore the integration of LLMs with marketing, recommendation, and advertising — including self-trained Transformers, generative recommendation, generative marketing, marketing agents, cross-lingual financial intent, and AI-driven automated strategy/modeling. Encourage algorithmic innovation, deepen a diverse and cutting-edge algorithmic tech stack, and stay at the forefront of industry developments. Leverage the international business environment to access global business data, accumulate hands-on experience in international AI deployment, and build your competitiveness as an internationally-minded AI professional.

Job Requirements

Master's degree or above, class of 2027 graduates. Computer Science, Machine Learning, Data Mining, and related majors preferred.

Solid grasp of data structures, machine learning, deep learning, and large models; proficiency with frameworks such as TensorFlow and PyTorch. Strong hands-on ability, fast learning, attentiveness to the latest technological advances, and a passion for AI.

Applied algorithms: experience in algorithm applications across marketing, recommendation, advertising, search, or large models is preferred; experience in financial business applications is a plus but not required. Prior experience with large-scale business deployment is preferred.

Foundational algorithms: solid command of one or more algorithmic theories, including deep learning, causal inference, time-series learning, graph learning, reinforcement learning, weakly supervised learning, NLP, KG, and LLM. Algorithmic innovation is a plus, as are international conference papers or competition achievements.