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Internship Recommender Systems Jobs (NOW HIRING)

... systems - spanning search, personalization, recommendation, and ranking - that power our marketplace and help our customers thrive. We are hiring Data Science interns across several teams and are ...

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Internship Recommender Systems information

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$42

How much do internship recommender systems jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for internship recommender systems in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is the difference between Internship Recommender Systems vs Data Analyst?

AspectInternship Recommender SystemsData Analyst
Required CredentialsTypically a background in computer science, data science, or related fields; familiarity with machine learning and recommender algorithmsDegree in statistics, mathematics, or related fields; proficiency in data analysis tools and programming languages
Work EnvironmentTech companies, startups, or online platforms focusing on personalized recommendationsBusiness, finance, healthcare, or marketing sectors analyzing data to inform decisions
Employer & Industry UsageUsed by companies developing recommendation engines for internships or job matching platformsEmployed across various industries to interpret data, generate reports, and support strategic decisions

Internship Recommender Systems focus on developing algorithms to match candidates with internships, requiring technical skills in machine learning. Data Analysts interpret and analyze data to support business decisions, often using statistical tools. While both roles involve working with data, their applications and skill sets differ significantly.

What are internship recommender systems?

Internship recommender systems are digital tools or algorithms designed to help students and job seekers find internship opportunities that best match their skills, interests, and qualifications. By analyzing user profiles, preferences, and sometimes even past experiences, these systems suggest internships that are likely to be a good fit. They often use machine learning or artificial intelligence techniques to personalize recommendations and improve the matching process over time. Such systems are widely used by universities, career platforms, and large organizations to streamline the internship search and application process.

What types of projects can I expect to work on during an internship focused on recommender systems?

As an intern working on recommender systems, you’ll typically contribute to projects such as improving recommendation algorithms, analyzing user interaction data, and testing new personalization features. You might also collaborate with data scientists and engineers to prototype and evaluate models, conduct A/B tests to measure recommendation performance, and help refine data pipelines. The work often involves both independent research and teamwork, giving you exposure to a blend of technical implementation and real-world problem-solving in a collaborative environment.

What are the key skills and qualifications needed to thrive as an Internship Recommender Systems Engineer, and why are they important?

To excel as an Internship Recommender Systems Engineer, a strong background in computer science, statistics, and machine learning, often supported by relevant coursework or experience, is essential. Familiarity with programming languages like Python, data analysis libraries, machine learning frameworks (such as TensorFlow or PyTorch), and recommendation system algorithms is typically required. Analytical thinking, problem-solving skills, and the ability to collaborate effectively with teams help candidates stand out. These skills are crucial for designing, implementing, and optimizing recommendation systems that deliver accurate and personalized suggestions to users.
More about Internship Recommender Systems jobs
What cities are hiring for Internship Recommender Systems jobs? Cities with the most Internship Recommender Systems job openings:
What are the most commonly searched types of Recommender Systems jobs? The most popular types of Recommender Systems jobs are:
What states have the most Internship Recommender Systems jobs? States with the most job openings for Internship Recommender Systems jobs include:
Infographic showing various Internship Recommender Systems job openings in the United States as of June 2026, with employment types broken down into 6% Internship, 33% As Needed, 50% Part Time, and 11% Nights. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.
2026 Fall Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Learni...

2026 Fall Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Learni...

Amazon

Seattle, WA • On-site

Full-time

Medical, Retirement

Posted 29 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,839 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


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 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.
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
- Experience programming in Java, C++, Python or related language
- Work 40 hours/week minimum and commit to 12 week internship minimum
- 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
PREFERRED QUALIFICATIONS
- Have publications at top-tier peer-reviewed conferences or journals
- Experience building machine learning models or developing algorithms for business application
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow
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. Final starting pay will be based on factors including experience, qualifications, and location. 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.
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US