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Graph Neural Network Internship Jobs in Seattle, WA

Electronic Arts (EA)

Applied AI Researcher

Kirkland, WA · On-site

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

Workday

Senior/Principal AI Engineer

Seattle, WA · On-site

$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 ...

Cisco

Applied AI Scientist

Bellevue, WA · On-site

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 ...

Cisco

Applied AI Scientist

Seattle, WA · On-site

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 ...

Workday

Principal AI Engineer

Seattle, WA

... 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 ...

Workday, Inc.

Principal AI Engineer

Seattle, WA · On-site

... 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 ...

Amazon

Applied Scientist II - AMZ9971140

Seattle, WA · 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.

Amazon

Senior Machine Learning Compiler Engineer

Seattle, WA · 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 ...

Meta

AI Research Scientist, Robotics

Redmond, WA

$154K/yr

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 ...

Meta

AI Research Scientist, Robotics

Redmond, WA

$219K/yr

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 ...

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All JobsGraph Neural Network JobsGraph Neural Network Internship JobsGraph Neural Network Internship Jobs in Seattle, WA

Graph Neural Network Internship information

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

As of Aug 3, 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 are popular job titles related to Graph Neural Network Internship jobs in Seattle, WA? For Graph Neural Network Internship jobs in Seattle, WA, the most frequently searched job titles are:
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Graph Neural Network Internship jobs near you
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 (EA)

Kirkland, WA • On-site

Full-time

Posted 23 days ago

Job description

Job Summary:
Electronic Arts (EA) creates next-level entertainment experiences that inspire players and fans globally. They are seeking a Senior AI/ML Research Scientist to advance Generative AI capabilities, focusing on developing and optimizing state-of-the-art AI models for creative content generation.
Responsibilities:
• 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:
Required:
• 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:
• 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.
Company:
Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Founded in 1982, the company is headquartered in Redwood City, USA, with a team of 10001+ employees. The company is currently Late Stage.

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