2027 Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Learning) - United States, PhD Student Science Recruiting
Core
PhD intern developing cutting-edge AI solutions for recommender systems and information retrieval to shape personalized experiences for millions of customers.
Role type
PhD Applied Science Intern (Recommender Systems/Information Retrieval)
Builds
Production ML models for product recommendations, personalized search, and information retrieval
Domain
E-commerce, Machine Learning, Information Retrieval
Deliverable
production ML models
Required skills
Python, Java, Spark, Knowledge Graphs, Neural Networks/GNNs, Time Series, Deep Learning, Large Language Models, Data Structures and Algorithms, Graph Modeling, Collaborative Filtering, Learning to Rank
Preferred skills
Publications at top-tier conferences, building ML models for business applications, implementing algorithms with PyTorch/Spark, using AI-assisted development tools
Technologies
PyTorch, Spark, Knowledge Graphs, GNNs, LLMs
Responsibilities
Design and evaluate new recommendation/search algorithms; Develop scalable data processing pipelines; Conduct research in recommender systems and information retrieval; Integrate solutions into production systems; Communicate findings via presentations and publications
Seniority
PhD Student, Research & Development