2027 Summer Applied Science Internship - Information & Knowledge Management (Machine Learning)- United States, PhD Student Science Recruiting

Amazon is hiring a 2027 Summer Applied Science Internship - Information & Knowledge Management (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

On Level's scale, this HR role is Builds AI ●●●●: the job is building AI systems.
Pay on this posting starts 8% higher than the typical HR posting on Level.
The posting mentions Python, PyTorch 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

Develop systems and frameworks for machine learning asset discovery and natural language processing as an Applied Science Intern.

PythonPyTorchTensorFlow

nlpmachine-learningknowledge-graphsdeep-learninglarge-language-models

Unleash Your Potential at the Forefront of AI Innovation

At Amazon, we're on a mission to revolutionize the way the world leverages machine learning. Amazon is seeking graduate student scientists who can turn revolutionary theory into awe-inspiring reality. As an Applied Science Intern focused on Information and Knowledge Management in Machine Learning, you will play a critical role in developing the systems and frameworks that power Amazon's machine learning capabilities. You'll be at the epicenter of this transformation, shaping the systems and frameworks that power our cutting-edge AI capabilities.

Imagine a role where you develop intuitive tools and workflows that empower machine learning teams to discover, reuse, and build upon existing models and datasets, accelerating innovation across the company. 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.

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, 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

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 business problems. 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
- Develop scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Design, development and evaluation of highly innovative ML models for solving complex business problems.
- Research and apply the latest ML techniques and best practices from both academia and industry.
- Think about customers and how to improve the customer delivery experience.
- Use and analytical techniques to create scalable solutions for business problems.

Basic qualifications

- Are enrolled in a PhD
- Can relocate to where the internship is based
- Experience programming in Java, C++, Python or related language
- 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
- Must be available for full-time (40 hours per week) internship for the whole duration of the internship
- 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

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 Summer Applied Science Internship - Information & Knowledge Management (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.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ 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.

Key facts

2027 Summer Applied Science Internship - Information & Knowledge Management (Machine Learning)- United States, PhD Student Science Recruiting is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $136k a year.
The role is based in US, WA, Seattle.
The job was posted on September 30, 2026.
Seniority: intern.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPMachine learningKnowledge GraphsDeep learningLarge Language ModelsPythonPyTorchTensorFlow

Also common in HR jobs at this level

Computer vision Generative AI Reinforcement learning AI agents PyTorch

Pay

This job starts at: $136k
Typical HR job: $126k

This posting starts 8% above the typical HR job. See HR jobs

Questions you could be asked

What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where knowledge graphs was part of your work. What did you do?
Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where large language models was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: NLP, Machine learning, Knowledge Graphs, Deep learning, and Large Language Models. 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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