2027 Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Learning) - United States, PhD Student Science Recruiting

What you'll do

• Design, implement, and evaluate recommendation and search algorithms using large-scale datasets.
• Develop scalable data pipelines for model training and collaborate on integrating solutions into production.
• Research advances in recommender systems and information retrieval, and communicate findings through presentations, documentation, or publications.

What they ask for

• Be enrolled in a PhD program.
• Be able to relocate to the internship location and commit to at least 40 hours per week for at least 12 weeks.
• Have programming experience in Python and, where applicable, Java or Spark, plus experience in one or more listed areas such as machine learning, NLP, deep learning, or knowledge graphs.
• Demonstrate research depth through publications, thesis work, or equivalent contributions.

Nice to have

• Publications in top-tier peer-reviewed conferences or journals.
• Experience building ML models or algorithms for business applications, using modern ML/data toolkits, or AI-assisted development tools.

Pay

135,660.00 USD Annually (base salary)

Tools

Python, Java, Spark, PyTorch

AI focus

Research and develop machine learning methods for recommendations, search, information retrieval, and related applications; use AI-powered tools to accelerate research, experimentation, and prototyping, and validate their outputs.