Applied Science Intern: Recommender Systems & IR

Amazon Inc.; Seattle (WA); On-site; USD 135,000 - 136,000; Full time

Benefits offered by this job

Mentorship from industry experts

Access to state-of-the-art computing

Job summary

Amazon is seeking an Applied Science Intern focused on Recommender Systems and Information Retrieval in Machine Learning. You’ll work with world‑class researchers to develop novel ML models and scalable pipelines, tackling NLP, DL, and large‑scale data tasks that impact millions of Amazon customers.

You will contribute to knowledge graphs, graph modeling, and ranking algorithms while collaborating with cross‑functional teams.

Qualifications

• PhD student enrolled and able to relocate to internship location.
• Work 40 hours/week minimum for 12 weeks.
• Experience programming in Python, and one or more of Java or Spark.
• Experience with Knowledge Graphs, NLP, ML, DL, LLMs, and related ML tasks.

Responsibilities

• Design and evaluate new recommender and search algorithms on large datasets.
• Develop scalable data pipelines for model training.
• Conduct research on recommender systems and information retrieval advancements.
• Collaborate with cross-functional teams to productionize solutions used by millions.
• Communicate findings through presentations and technical docs.

Skills

Python

Java

Spark

Knowledge Graphs

Information Retrieval

Machine Learning

Natural Language Processing

Deep Learning

Large Language Models

Neural Networks/GNNs

Data Structures and Algorithms

Programming/Scripting Languages

Tools

PyTorch

Apache Spark

Job description

Amazon is seeking an Applied Science Intern focused on Recommender Systems and Information Retrieval in Machine Learning. You’ll work with world‑class researchers to develop novel ML models and scalable pipelines, tackling NLP, DL, and large‑scale data tasks that impact millions of Amazon customers.

You will contribute to knowledge graphs, graph modeling, and ranking algorithms while collaborating with cross‑functional teams.