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

Amazon Science; Seattle (WA); On-site; USD 115,000 - 156,000; Full time

Benefits offered by this job

EAP

Mental Health Support

Medical Advice Line

401(k) matching

Job summary

Amazon invites applications for a full‑time 12‑week AI Applied Science Internship focused on recommender systems and information retrieval. You will work with leading researchers on deep learning, NLP, and large‑scale systems to advance production‑grade ML assets.

Ideal candidates are PhD students who can relocate, commit to 40h/week, and engage in cross‑functional collaboration with mentorship from industry leaders.

Qualifications

• PhD enrollment and willingness to relocate to base location.
• Work 40 hours/week for a 12-week internship.
• Experience in Python and one or more of the following: Knowledge Graphs, Neural Networks, ML, NLP, DL, LLMs, Graph Modeling.

Responsibilities

• Design, implement, and evaluate new recommendation/search algorithms on large datasets.
• Develop scalable data pipelines for model training.
• Research advances in recommender systems, information retrieval, and ML.
• Collaborate with cross-functional teams to deploy solutions affecting millions of users.
• Present findings via demos, docs, and potential publications.

Skills

Python

Java

Spark

Knowledge Graphs

Neural Networks

NLP

Deep Learning

GNNs

LLMs

Data Structures

Algorithms

Education

PhD candidate

Tools

PyTorch

Spark

Feature Engineering

Job description

Unleash Your Potential as an AI Trailblazer

At Amazon, we're on a mission to revolutionize the way people discover and access information. Our Applied Science team is at the forefront of this endeavor, pushing the boundaries of recommender systems and information retrieval. We're seeking brilliant minds to join us as interns and contribute to the development of cutting-edge AI solutions that will shape the future of personalized experiences.

As an Applied Science Intern focused on Recommender Systems and Information Retrieval in Machine Learning, you'll have the opportunity to work alongside renowned scientists and engineers, tackling complex challenges in areas such as deep learning, natural language processing, and large-scale distributed systems. Your contributions will directly impact the products and services used by millions of Amazon customers worldwide.

Imagine a role where you immerse yourself in groundbreaking research, exploring novel machine learning models for product recommendations, personalized search, and information retrieval tasks. You'll leverage natural language processing and information retrieval techniques to unlock insights from vast repositories of unstructured data, fueling the next generation of AI applications.

Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated.

Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology.

Must be eligible and available for a full-time (40h / week) 12 week internship between May 2026 and September 2026.

Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA.

Key job responsibilities

We are particularly interested in candidates with expertise in:

• Knowledge Graphs and Extraction
• Programming/Scripting Languages
• Time Series
• Machine Learning
• Natural Language Processing
• Deep Learning
• Neural Networks/GNNs
• Large Language Models
• Data Structures and Algorithms
• Graph Modeling
• Collaborative Filtering
• Learning to Rank
• Recommender Systems

In this role, you'll collaborate with brilliant minds to develop innovative frameworks and tools that streamline the lifecycle of machine learning assets, from data to deployed models in areas at the intersection of Knowledge Management within Machine Learning. You will conduct groundbreaking research into emerging best practices and innovations in the field of ML operations, knowledge engineering, and information management, proposing novel approaches that could further enhance Amazon's machine learning capabilities.

The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex problems, and to communicate research findings clearly. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment.

Leverage AI-powered tools where applicable to accelerate research, experimentation, and prototyping. Critically review and validate outputs from AI tools and automated systems.

A day in the life

• Design, implement, and experimentally evaluate new recommendation and search algorithms using large-scale datasets
• Develop scalable data processing pipelines to ingest, clean, and featurize diverse data sources for model training
• Conduct research into the latest advancements in recommender systems, information retrieval, and related machine learning domains
• Collaborate with cross-functional teams to integrate your innovative solutions into production systems, impacting millions of Amazon customers worldwide
• Communicate your findings through captivating presentations, technical documentation, and potential publications, sharing your knowledge with the global AI community

Basic Qualifications

• Are enrolled in a PhD
• Can relocate to where the internship is based
• Work 40 hours/week minimum and commit to 12 week internship minimum
• Experience programming in Python, and where applicable, Java or Spark Experience with one or more of the following: Knowledge Graphs and Extraction, Neural Networks/GNNs, Data Structures and Algorithms, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Large Language Models, Graph Modeling, Knowledge Graphs and Extraction, Programming/Scripting Languages
• Demonstrated science depth in a specific research area, evidenced through publications, thesis work, or equivalent contributions

Preferred Qualifications

• Have publications at top-tier peer-reviewed conferences or journals
• Experience building machine learning models or developing algorithms for business application
• Experience implementing algorithms using modern ML and data toolkits (e.g. PyTorch, Spark, feature engineering frameworks, or recommendation libraries)
• Experience with AI-assisted development tools to accelerate research, coding, or evaluation

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

The starting pay for this position is listed below. Starting Day 1 of employment, Amazon offers

• EAP
• Mental Health Support
• Medical Advice Line
• 401(k) matching

Learn more about our benefits at https://hiring.amazon.com/why-amazon/benefits.

Seattle, WA, USA - 135,660.00 USD Annually