Description
The Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.
About the Team:
The Shopee Ads team is dedicated to driving commercial growth across e-commerce, video, gaming, and other diverse scenarios through cutting-edge algorithmic technology. We leverage advanced algorithm models to precisely connect users with advertisers, optimize traffic allocation and matching efficiency, and continuously enhance the platform's monetization capabilities. The team's core technical domains cover ad retrieval, ranking, mechanism strategy, content supply, and ecosystem development.
Job Description:
- Deeply understand business scenarios and apply frontier technologies — including deep learning, reinforcement learning, causal inference, and large language models — to improve ad delivery intelligence and key performance metrics.
- Participate in the strategic iteration and innovation of core advertising algorithm modules, such as retrieval, ranking models, bidding mechanisms, creative optimization, and advertiser growth.
- Participate in the design and development of large-scale distributed machine learning / deep learning systems, driving algorithm engineering implementation and systematic capability building.
- Stay current with advances in AI, NLP, computer vision, and related fields; explore and apply innovative algorithms to drive sustained business growth.
Requirements:
- Master's degree or above in Computer Science, Artificial Intelligence, or a related field
- At least 1 year of core algorithm R&D experience in internet advertising, search, or recommendation systems
- Strong programming fundamentals with proficiency in at least one of Python, C++, or Java, as well as SQL; solid understanding of data structures and algorithms.
- Familiarity with mainstream big data processing platforms (e.g. Spark, Flink, Hadoop) and machine learning / deep learning frameworks (e.g. TensorFlow, PyTorch, Scikit-learn).
- Substantial research and practical experience in at least one of the following areas: computational advertising, recommendation systems, machine learning, deep learning, reinforcement learning, NLP, or computer vision.
- Excellent logical thinking, data analysis, problem-solving, and innovation skills; ability to contribute to the design and delivery of complex algorithm projects.
- Strong communication and collaboration skills, a high sense of ownership, self-motivation, and a passion for learning; embraces challenges and pursues excellence.
Preferred Qualifications
- Publications at top international conferences (e.g. KDD, NeurIPS, ICML, CVPR, ACL) or in high-quality journals.
- Proven track record of successfully delivering algorithm projects in complex business environments at large internet companies, with measurable business impact.