Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
2027 Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Learning) - United States, PhD Student Science Recruiting
Seattle, Washington, USA
Actively hiring, first seen by us 1 day ago- Pay
Pay amount needs review — pay source
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
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: full-time
From the employer’s posting
Before you apply
- New graduates
- For current students
- Are enrolled in a PhD
- Employer’s visa record
- 31,079 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.
What you’ll work on
Full postingDesign, implement and experimentally evaluate new recommendation and search algorithms
Build scalable data pipelines to ingest, clean and featurize data for model training
Research advances in recommender systems, information retrieval and related ML
Work with cross-functional teams to move solutions into production systems
Present findings through presentations, technical documentation and possible publications
From the employer’s posting
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
Communicate your findings through captivating presentations, technical documentation, and potential publications
Education & alternatives
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
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 13, 20261 day ago
- Recorded sightings
- 3
- Last seen by us
- Nov 15, 2026
- Employer says posted
- Sep 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 1
Early. Similar jobs usually come down between day 8 and day 76.
From 5,516 similar postings that came down. Coming down is not always a hire.
Amazon is hiring
550 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Java
- Python
- Spark
- PyTorch
Where the posting names them
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
- 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.
Your next step
Complete your application on www.amazon.jobs. The employer’s form will show what is required.
Already applied? Track this application
About Amazon
- People
- About 1,207,759 in 2024.Benefit plan filings (Form 5500)
- Company
- Listed as AMZN.
- H-1B visas
- 6,217 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
- Layoff notices
- Notices this year and last cover 2,978 people. The latest was filed November 2, 2026.State WARN notices
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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
- 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
- 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.
Seattle, WA, USA - 135,660.00 USD Annually
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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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
- Location & working pattern
Seattle, Washington, USA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.