1

Graph Neural Network Internship Jobs in Seattle, WA

Research and implement Graph Neural Network (GNN) architectures to model complex relationships, knowledge graphs, recommendation systems, and structured data representations. * Evaluate emerging ...

... Graph Neural Network (GNN) architectures to model complex relationships, knowledge graphs, recommendation systems, and structured data representations. โ€ข Evaluate emerging research and rapidly ...

Senior/Principal AI Engineer

Seattle, WA

$142K - $196K/yr

... and/or graph neural network models for real-world use cases * 6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.) * Proven track record of successfully leading ...

Our work spans networking, security, observability, and customer experience - designing and ... Large-scale graph representation learning and Graph Neural Networks (GNNs) (e.g., GCN/GAT/GraphSAGE ...

Our work spans networking, security, observability, and customer experience - designing and ... Large-scale graph representation learning and Graph Neural Networks (GNNs) (e.g., GCN/GAT/GraphSAGE ...

... and/or graph neural network models for real-world use cases * 6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.) * Proven track record of successfully leading ...

... and/or graph neural network models for real-world use cases * 6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.) * Proven track record of successfully leading ...

Applied Scientist II - AMZ9971140

Seattle, WA ยท On-site

$153K - $193K/yr

Extend and apply deep learning architectures (e.g., graph neural networks, transformers, recurrent ... network configuration verification, resource compliance checking, and system reliability assurance.

Senior Machine Learning Compiler Engineer

Seattle, WA ยท On-site

$139K - $183K/yr

... neural network descriptions created in frameworks such as TensorFlow, PyTorch, and MXNET, and ... About the team BASIC QUALIFICATIONS - 5+ years of non-internship professional software development ...

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 ...

next page

Showing results 1-20

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 Jul 31, 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 July 2026, with employment types broken down into 66% Full Time, 30% Part Time, and 4% Contract. Highlights an 63% Physical, 3% Hybrid, and 34% Remote job distribution, with an average salary of $41,270 per year, or $19.8 per hour.

Applied AI Researcher

Electronic Arts Inc.

Kirkland, WA โ€ข On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 11 days ago


Job description

General Information
Locations: Kirkland, Washington, United States of America
  • Location: Kirkland
  • State: Washington
  • Country: United States of America

Role ID
214205
Worker Type
Regular Employee
Studio/Department
Experiences
Work Model
Hybrid
Description & Requirements
Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.
EA Experiences group (XO) is dedicated to ensuring great experiences for our growing communities centered around our world-renowned brands, including fan-favorites like Apex, Battlefield, EA SPORTS FC, Madden NFL and The Sims, just to name a few. We're a multi-functional group, with world-class expertise building fandoms, driving interactive storytelling, and positioning our franchises at the center of the broader entertainment ecosystem. We inspire, connect, and engage fans through culturally relevant content, intentionally architected journeys across channels, and meaningful fan care. Our goal is to provide valuable, easy experiences that fans love - in our games, around our games, and through innovative adjacent experiences to grow and enrich how fans experience EA as we shape the future of entertainment.
To empower more players and fans in new and amazing ways, we need more innovators to join our world-class team. The future of entertainment is interactive, and you can help lead that future, by growing and enriching how hundreds of millions of people (and counting) find joy and belonging, forge friendships, and celebrate their lived experiences through the work we do every single day, together.
About the Role
We are seeking a Senior AI/ML Research Scientist to advance the next generation of Generative AI capabilities across creative content generation and foundation models. This role will focus on developing, adapting, and optimizing state-of-the-art AI models, including diffusion models, LLMs, multimodal architectures, and Graph Neural Networks (GNNs).
You will drive research and development efforts and model architectures that enable scalable, high-quality content generation. The ideal candidate combines deep scientific expertise with hands-on experience building and training large-scale machine learning systems.
Working closely with cross-functional teams of engineers, product leaders, and domain experts, you will help define the organization's AI strategy and deliver breakthrough capabilities that leverage advances in GenAI and Deep Learning.
What You'll Do
  • Lead research and development of state-of-the-art generative AI systems, including diffusion models, latent diffusion architectures, and multimodal foundation models.
  • Collaborate with stakeholders to understand business needs and translate them into model requirements. Advise on what is possible and the impact that the models can drive.
  • Design, train, fine-tune, and optimize large-scale AI models for creative content generation.
  • Develop and apply parameter-efficient adaptation techniques, including LoRA, adapters, prompt tuning, and related methods for foundation model customization.
  • Advance internal LLM capabilities through model training, fine-tuning, evaluation, alignment, and optimization.
  • Research and implement Graph Neural Network (GNN) architectures to model complex relationships, knowledge graphs, recommendation systems, and structured data representations.
  • Evaluate emerging research and rapidly prototype innovative approaches from leading conferences and publications.
  • Collaborate with engineering teams to transition research innovations into scalable production systems.

Qualifications
Minimum Qualifications
  • PhD or Master's in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
  • 7+ years of experience conducting advanced machine learning research and development with a track record of translating cutting-edge research into impactful products or platforms.
  • Strong publication record in leading AI conferences or journals (NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP, KDD, AAAI, or equivalent).
  • Deep expertise in deep learning fundamentals, optimization, representation learning, and neural network architectures.
  • Strong programming skills in Python and experience with modern ML frameworks such as PyTorch, JAX, or TensorFlow.
  • Experience in training and evaluating large-scale machine learning models on distributed compute infrastructure and GPU-accelerated computing environments
Preferred Qualifications
  • Expertise in developing and training diffusion models, latent diffusion models, or related generative architectures.
  • Experience fine-tuning foundation models using LoRA, QLoRA, adapters, PEFT techniques, RLHF, DPO, or similar approaches.
  • Experience developing generative AI systems for image, video, audio, 3D, or other creative content domains.

Pay Transparency - North America
COMPENSATION AND BENEFITS
The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs).
PAY RANGES
* Washington (depending on location e.g. Seattle vs. Spokane) *$133,100 - $178,400 USD
Pay is just one part of the overall compensation at EA.
In the US, we offer a package of benefits including paid time off (3 weeks per year to start), 80 hours per year of sick time, 16 paid company holidays per year, 10 weeks paid time off to bond with baby, medical/dental/vision insurance, life insurance, disability insurance, and 401(k) to regular full-time employees. Certain roles may also be eligible for bonus and equity.
About Electronic Arts
We're proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.
We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.
Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.