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Amazon

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

Amazon is hiring a 2027 Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Learning) - United States, PhD Student Science Recruiting in Seattle, United States. It pays $136k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

  • Builds AI ●●●● is how Level rates this HR role: the job is building AI systems.
  • Pay on this posting starts 9% higher than the typical HR posting on Level.
  • The posting mentions PyTorch, Python and TensorFlow among its tools and skills.
  • Level classes it as an internship.
  • Amazon has 20,000+ other open roles on Level.

AI in this role

Conduct applied research and develop machine learning models for recommender systems and information retrieval.

PyTorchPythonTensorFlow
nlpmachine-learningrecommender-systemsnatural-language-processingdeep-learning
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

How we rate this

2027 Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Learning) - United States, PhD Student Science Recruiting at Amazon rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPMachine learningRecommender SystemsNatural Language ProcessingDeep learningPyTorchPythonTensorFlow

Pay

This job starts at
$136k
Typical HR job
$124k

This posting starts 9% above the typical HR job. See HR jobs

Questions you could be asked

  1. What NLP problem have you worked on, and how did you measure whether it actually worked?
  2. Tell me about a project where machine learning was part of your work. What did you do?
  3. Tell me about a project where recommender systems was part of your work. What did you do?
  4. Tell me about a project where natural language processing was part of your work. What did you do?
  5. Tell me about a project where deep learning was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: NLP, Machine learning, Recommender Systems, Natural Language Processing, and Deep learning. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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