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Machine Learning Unpaid Internship Jobs (NOW HIRING)

Internship, academic project, or personal project experience in machine learning * Familiarity with Git and version control * Exposure to cloud platforms (AWS, Azure, or Google Cloud) * Basic ...

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

About the Role: Engineers on the BCI team utilize signal processing and machine learning to ... Temporary Employees & Interns excluded

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

About the Role: Engineers on the BCI team utilize signal processing and machine learning to ... Temporary Employees & Interns excluded

WGHP-TV, serving the Piedmont-Triad region of North Carolina, is offering an unpaid internship for ... flow Learning how to stack shows, manage breaking news, and update digital content Observing ...

... on academic, internship, personal, or professional projects. - Strong Python foundation and hands-on experience with at least one machine learning library or framework such as scikit-learn ...

Showing results 41-60

Machine Learning Unpaid Internship information

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$25.5K

$42.6K

$88K

How much do machine learning unpaid internship jobs pay per year?

As of Aug 16, 2026, the average yearly pay for machine learning unpaid internship in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is a machine learning unpaid internship?

A Machine Learning Unpaid Internship is a temporary position where students or recent graduates work with professionals to gain practical experience in machine learning without receiving monetary compensation. Interns typically assist with data analysis, model development, and research tasks, while learning about real-world machine learning applications. These internships help individuals build relevant skills, expand their professional network, and improve their resumes for future job opportunities.

What kinds of projects and responsibilities can I expect during a machine learning unpaid internship?

As a machine learning unpaid intern, you will typically work on projects such as data preprocessing, model training, and performance evaluation under the guidance of experienced team members. Your daily tasks may include cleaning datasets, implementing algorithms, and conducting experiments to test model improvements. Interns often collaborate with data scientists and engineers, participating in team meetings and code reviews to learn best practices. This hands-on experience provides valuable exposure to real-world machine learning workflows and tools, helping you build skills that are essential for future roles in the field.

What are the key skills and qualifications needed to thrive as a machine learning unpaid intern, and why are they important?

To thrive as a Machine Learning Unpaid Intern, you should have a solid understanding of linear algebra, statistics, and programming languages like Python, along with coursework or experience in machine learning concepts. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is typically expected. Strong problem-solving skills, eagerness to learn, and effective communication set standout interns apart. These skills are essential for contributing to projects, adapting quickly in a dynamic field, and collaborating with team members on real-world machine learning challenges.

What is the difference between Machine Learning Unpaid Internship vs Data Science Intern?

AspectMachine Learning Unpaid InternshipData Science Intern
Required CredentialsBasic programming, coursework in ML or AIStatistics, programming, data analysis skills
Work EnvironmentStartups, tech companies, research labsTech firms, consulting agencies, research institutions
Industry UsageFocus on ML model development and algorithmsBroader data analysis, visualization, reporting

The main difference is that a Machine Learning Unpaid Internship emphasizes developing ML models and algorithms, often requiring knowledge of programming and AI concepts. In contrast, a Data Science Intern role covers a wider range of data analysis tasks, including visualization and reporting. Both roles are common in tech and research environments, but the internship focus and skill requirements differ slightly.

More about Machine Learning Unpaid Internship jobs

What cities are hiring for Machine Learning Unpaid Internship jobs?

Cities with the most Machine Learning Unpaid Internship job openings:

What states have the most Machine Learning Unpaid Internship jobs?

States with the most job openings for Machine Learning Unpaid Internship jobs include:

What job categories do people searching Machine Learning Unpaid Internship jobs look for?

The top searched job categories for Machine Learning Unpaid Internship jobs are:

Infographic showing various Machine Learning Unpaid Internship job openings in the United States as of August 2026, with employment types broken down into 33% Internship, 11% Full Time, and 56% Part Time. Highlights an 100% In-person job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

2026 Fall Applied Science Internship - Information & Knowledge Management (Machine Learning) - Unite

Amazon

Seattle, WA • On-site

Full-time

Medical, Retirement

Re-posted 3 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,091 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

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.
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
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

What Amazon employees say

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Hours and flexibility

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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