Ecommerce Recommendation Engineer

2 weeks ago

Singapore beBeeDataScientist Full time $80,000 - $120,000
Are you a problem-solver with expertise in software development and data science? Do you want to utilize machine learning techniques for business-impacting solutions? We are seeking a talented graduate to join our team of applied machine learning engineers and data scientists in E-commerce recommendations.

Our team focuses on developing innovative algorithms and techniques to improve user engagement and satisfaction. We aim at connecting all customers to excellent sellers and quality products on TikTok Shop through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. As a member of this team, you will work on building largescale ecommerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc.

Responsibilities:
  • Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems.
  • Build long and short-term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.
  • Design, develop, evaluate, and iterate on predictive models for candidate generation and ranking.
  • Design and build supporting/debugging tools as needed.
  • Support the production of scalable and optimized AI/machine learning (ML) models.
  • Focus on building algorithms for the extraction, transformation, and loading of large volumes of real-time, unstructured data to deploy AI/ML solutions.
  • Run experiments to test the performance of deployed models, identify and resolve bugs that arise in the process.
Qualifications: We are looking for final year or recent graduates with a background in software development, computer science, computer engineering, or a related technical discipline. Strong programming and problem-solving skills, experience in applied machine learning, familiar with one or more algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep etc., and experience with at least one programming language like C++/Python or equivalent. Preferred qualifications include experience in recommendation system, online advertising, information retrieval, natural language processing, machine learning, largescale data mining, or related fields. Publications at KDD, NeurlPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDDcup etc.

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