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Graph Neural Network Internship Jobs in Seattle, WA

Develop algorithms based on state-of-the-art machine learning and neural network methodologies ... Demonstrated research and software engineering experience via an internship, work experience ...

Develop algorithms based on state-of-the-art machine learning and neural network methodologies ... Demonstrated research and software engineering experience via an internship, work experience ...

Senior AI Compiler Engineer, MLIR

Seattle, WA · On-site

$139K - $183K/yr

Develop MLIR-based graph representations and optimizations for future GPU architectures. Partner ... A track record of mentoring early career engineers and interns is a bonus With competitive salaries ...

Senior AI Compiler Engineer, MLIR

Seattle, WA · On-site

$139K - $183K/yr

Develop MLIR-based graph representations and optimizations for future GPU architectures. * Partner ... A track record of mentoring early career engineers and interns is a bonus With competitive salaries ...

Networking experience. * Professional distributed systems experience (internship experience is ... Knowledgeable in network topology, numerical optimization techniques, graph theory approaches, or ...

Showing results 21-40

Graph Neural Network Internship information

See Seattle, WA salary details

$10

$19

$29

How much do graph neural network internship jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for graph neural network internship in Seattle, WA is $19.84, according to ZipRecruiter salary data. Most workers in this role earn between $16.39 and $21.88 per hour, depending on experience, location, and employer.

What is a graph neural network internship?

A Graph Neural Network (GNN) Internship is a position designed for students or recent graduates to gain hands-on experience working with GNNs, a type of deep learning model that processes data structured as graphs. Interns typically participate in research, model development, and the application of GNNs to various problems such as social network analysis, recommendation systems, or molecular property prediction. The internship provides opportunities to collaborate with experienced researchers, learn cutting-edge techniques, and contribute to real-world projects involving graph-based machine learning.

What types of projects or tasks can I expect to work on during a graph neural network internship?

As a Graph Neural Network (GNN) intern, you will typically be involved in projects such as developing and optimizing GNN models for real-world datasets, implementing new neural network architectures, and conducting experiments to evaluate model performance. You may also assist with data preprocessing, feature engineering, and collaborating with data scientists and machine learning engineers to integrate GNN solutions into larger systems. Regular tasks include reviewing recent research, documenting findings, and presenting your results to the team. This internship offers an excellent opportunity to deepen your understanding of advanced machine learning methods while gaining hands-on experience in a collaborative research-focused environment.

What are the key skills and qualifications needed to thrive as a graph neural network intern, and why are they important?

To thrive as a Graph Neural Network Intern, you need a solid background in machine learning, data science, and programming languages such as Python, often supported by coursework or research experience in deep learning and graph theory. Familiarity with frameworks like PyTorch Geometric, TensorFlow, and libraries such as NetworkX, along with experience using Jupyter Notebooks and Git, is typically expected. Strong analytical thinking, problem-solving skills, and effective communication help interns collaborate with research teams and convey complex ideas clearly. These skills and qualifications are essential for contributing to cutting-edge AI projects and advancing research in graph-based machine learning.

What job categories do people searching Graph Neural Network Internship jobs in Seattle, WA look for?

The top searched job categories for Graph Neural Network Internship jobs in Seattle, WA are:

Infographic showing various Graph Neural Network Internship job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 12% Part Time, and 6% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $41,270 per year, or $19.8 per hour.

Sr. Product Manager - Tech, AI, R2L AI Product

Amazon

Bellevue, WA • On-site

$142K - $188K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,147 frontline employees who took The Breakroom Quiz

5th of 39 rated national retailers


Job description

The Opportunity
What if you could teach machines to make millions of delivery decisions - faster, smarter, and more efficiently than ever before. We're looking for a Senior Product Manager - Tech who's obsessed with the intersection of artificial intelligence and real-world operations to join Amazon's Sub Same Day team. This isn't about incremental optimization.

This is about building intelligent systems that autonomously orchestrate one of the most complex delivery networks on the planet - in real time, at massive scale.
You will define and drive the product roadmap for AI/ML-powered solutions across the Sub Same Day delivery network - from supply chain planning and real-time capacity allocation to delivery and anomaly detection. You'll identify high-impact business problems ripe for AI disruption, translate them into well-scoped technical product requirements, and build the business case to secure investment. Your multi-year product vision will leverage state-of-the-art techniques - large language models, reinforcement learning, computer vision, and graph neural networks - to fundamentally reimagine how last-mile delivery works at Amazon scale.
You will serve as the connective tissue between data scientists, system development engineers, business intelligence engineers - ensuring technical feasibility, architectural soundness, and delivery velocity

You'll own the end-to-end product lifecycle: from problem framing and data pipeline design through model development, A/B experimentation, production deployment, and continuous iteration. This means making hard trade-off decisions across model accuracy, latency, infrastructure cost, and customer experience - with a deep understanding of the technical constraints and opportunities. You'll drive technical debt reduction and platform scalability, ensuring AI systems are production-grade, fault-tolerant, and built for exponential growth.
You will partner with operations, logistics, finance, and science teams to ensure AI solutions are grounded in operational reality and deliver measurable business value

You'll influence senior leadership with data-driven narratives, translating complex ML concepts into clear strategic recommendations, and build scalable processes for feature prioritization, sprint planning, and release management across distributed engineering teams.
What Makes This Role Different
Your AI products will make decisions affecting millions of packages daily across Amazon's fastest-growing delivery channel. You'll work with large-scale ML platforms (SageMaker, custom training infrastructure), and production inference systems operating at sub-100ms latency. Sub Same Day is still early in its AI journey - you'll have the rare opportunity to define the foundational AI strategy from the ground up, not just optimize existing systems

From the data that feeds models to the customer experience those models create - you own the full stack of outcomes.
Key job responsibilities
- Lead the product strategy and roadmap for AI/ML initiatives in the Sub Same Day delivery network
- Orchestrate collaboration between data scientists, engineers, operations teams, and business stakeholders
- Define and prioritize product requirements based on customer needs and business impact
- Develop business cases and ROI analysis for new AI initiatives
- Drive technical requirement gathering and documentation
- Lead sprint planning and backlog prioritization sessions
- Monitor key performance metrics and adjust strategies based on data-driven insights
- Identify and resolve cross-team dependencies and conflicts
- Champion product innovations to senior leadership and key stakeholders
- Drive go-to-market/adoption strategies for new AI-powered features and capabilities
A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you


At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!


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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, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US