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Internship Graduate Machine Learning Jobs in Seattle, WA

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics * You have 1-2 years industry machine learning ...

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics * You have 1-2 years industry machine learning ...

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Internship Graduate Machine Learning information

See Seattle, WA salary details

$29K

$48.5K

$100.1K

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

As of Jul 30, 2026, the average yearly pay for internship graduate machine learning in Seattle, WA is $48,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,000.00 and $52,300.00 per year, depending on experience, location, and employer.

What is the difference between Internship Graduate Machine Learning vs Data Analyst?

AspectInternship Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; basic knowledge of programming and statisticsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentTech companies, research labs, startups; project-based, collaborative teamsBusiness, finance, marketing sectors; focus on reporting and data interpretation
Employer & Industry UsageUsed in tech, AI, and research industries for developing machine learning modelsCommon in corporate, finance, and consulting firms for data-driven decision making

While both roles involve working with data, an Internship Graduate Machine Learning focuses on developing algorithms and models using programming skills, often in tech environments. In contrast, a Data Analyst emphasizes interpreting data, creating reports, and supporting business decisions. The roles overlap in data handling but differ in technical depth and application focus.

What are the key skills and qualifications needed to thrive as an Internship Graduate in Machine Learning, and why are they important?

To thrive as an Internship Graduate in Machine Learning, you typically need a strong background in mathematics, programming (especially Python), and familiarity with algorithms and data structures, often supported by coursework or a degree in computer science, statistics, or a related field. Hands-on experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of tools such as Jupyter Notebooks and version control systems like Git, are highly valued. Curiosity, problem-solving, teamwork, and effective communication are crucial soft skills to excel in collaborative and innovative environments. These competencies enable interns to contribute to real-world projects, adapt to fast-changing technologies, and communicate findings clearly within interdisciplinary teams.

What are Internship Graduate Machine Learning positions?

Internship Graduate Machine Learning positions are entry-level roles designed for recent graduates or students who have completed coursework in machine learning, data science, or related fields. These internships provide hands-on experience working with real-world data, building and testing machine learning models, and collaborating with experienced professionals. Interns gain exposure to industry-standard tools and techniques, helping them bridge the gap between academic learning and practical application. Such positions are valuable for building a portfolio, networking, and enhancing job prospects in the rapidly growing field of artificial intelligence.

What types of projects do Internship Graduate Machine Learning roles typically involve, and how are responsibilities structured within the team?

Internship Graduate Machine Learning roles often focus on supporting ongoing research or development projects, such as building predictive models, cleaning and analyzing data, or prototyping algorithms. Interns usually collaborate closely with data scientists and engineers, contributing to specific project milestones while learning best practices in model development and deployment. Responsibilities are often structured to allow for mentorship and feedback, with interns participating in regular team meetings, code reviews, and brainstorming sessions. This collaborative environment provides valuable exposure to real-world machine learning workflows and helps interns build both technical and soft skills relevant to the field.
What are the most commonly searched types of Graduate Machine Learning jobs in Seattle, WA? The most popular types of Graduate Machine Learning jobs in Seattle, WA are:
What are popular job titles related to Internship Graduate Machine Learning jobs in Seattle, WA? For Internship Graduate Machine Learning jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Internship Graduate Machine Learning jobs in Seattle, WA look for? The top searched job categories for Internship Graduate Machine Learning jobs in Seattle, WA are:
Infographic showing various Internship Graduate Machine Learning job openings in Seattle, WA as of July 2026, with employment types broken down into 2% As Needed, 77% Full Time, 18% Part Time, and 3% Contract. Highlights an 98% Physical, and 2% Remote job distribution, with an average salary of $48,461 per year, or $23.3 per hour.

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

Amazon

Seattle, WA • On-site

Full-time

Medical, Retirement

Re-posted 15 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,023 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

Pay

Benefits

Hours and flexibility

Workplace

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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