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Singapore

Algorithm Engineer, Recommendation (Campus Recruitment 2026)

Shopee
$49,584 - $62,785 a year
Singapore
1 day ago

Department Engineering and Technology
LevelEntry Level
LocationSingapore

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 E-commerce Recommendation Algorithm Team is dedicated to enhancing the user experience across all recommendation scenarios, supporting a rapidly growing user and product base. Our mission is to build a world-class recommender system using cutting-edge technologies, driving continuous performance improvements, and exploring best practices for large-scale deep neural network-based systems.

If you are passionate about e-commerce, data, and recommender systems, we welcome you to join us and help shape the next-generation recommendation platform for millions of users.
Job Description:
As an Algorithm Engineer, you will:
  • Algorithm Development: Contribute to the design and development of innovative recommendation algorithms to improve user experience and conversion rates.
  • Model Optimization: Assist in optimizing models to enhance efficiency, accuracy, and scalability.
  • Data Analysis: Analyze user behavior data to uncover patterns and improve recommendation performance.
  • Business Alignment: Translate business goals into algorithmic solutions that deliver measurable impact.
  • Learning & Innovation: Stay updated on the latest research and trends in recommender systems, and apply new methods where appropriate.
Requirements:
  • Bachelor’s degree or above in Computer Science, Artificial Intelligence, Data Science, or a related field (graduating from December 2025 to May 2026).
  • Strong programming skills, with proficiency in Python or C++ preferred.
  • Solid understanding of data structures, algorithms, and basic machine learning principles.
  • Familiarity with at least one deep learning framework (e.g., TensorFlow, PyTorch, MXNet) is a plus.
  • Passion for recommender systems, data-driven problem solving, and continuous learning.
  • Strong communication and teamwork skills; able to collaborate in a fast-paced environment.
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