About the Team:
The Shopee E-commerce Recommendation Algorithm Team is dedicated to enhancing the user experience across all recommendation scenarios amid a continuously growing user and product base. We are committed to building a world-class recommender system, leveraging cutting-edge technologies to drive performance improvements, and continuously exploring best practices for large-scale deep neural network-based recommender systems. If you share our passion for e-commerce and recommender systems, we invite you to join us in developing an unprecedented recommender system for e-commerce.
Job Description:
- Algorithm Development: Design and develop innovative recommendation algorithms tailored to various e-commerce scenarios to enhance user experience and conversion rates.
- Model Optimization: Continuously iterate and optimize existing models to improve efficiency, accuracy, and scalability.
- Data Analysis: Conduct in-depth analysis of user behavior data to uncover user preferences and improve model effectiveness.
- Business Insight: Understand business goals and design algorithmic solutions that align with and support these objectives.
- Innovation & Trends: Stay up-to-date with the latest developments in recommender systems and related technologies, and explore opportunities to integrate state-of-the-art (SOTA) methods.
Requirements:
- Bachelor’s degree or above in Computer Science or a related field
- Over 2 years of experience in search, recommendation, or advertising system
- Strong coding skills; familiar with Linux systems and proficient in C++ and/or Python
- Solid foundation in machine learning theory; familiar with common recommendation models; experienced with deep learning frameworks such as TensorFlow, Caffe, MXNet, or PyTorch
- Self-motivated, resilient under pressure, and eager to drive business breakthroughs.
- Excellent communication and teamwork skills
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