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Graph Neural Network Jobs (NOW HIRING)

$121K - $167K/yr

Artificial neural network training * Programming: Python, C++, MATLAB, Go, PyTorch, TensorFlow, Keras * Image processing * Building graph databases * Building PostgreSQL databases with vector store ...

Data Scientist III

Cassville, MO ยท On-site

$90K - $180K/yr

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

Staff, Data Scientist

Johnson, AR ยท Hybrid

$110K - $220K/yr

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

Senior, Data Scientist

Gravette, AR ยท On-site

$90K - $180K/yr

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

Staff, Data Scientist

Tontitown, AR ยท Hybrid

$110K - $220K/yr

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

Staff, Data Scientist

Springdale, AR ยท Hybrid

$110K - $220K/yr

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection ...

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Graph Neural Network information

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How much do graph neural network jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for graph neural network in the United States is $26.64, according to ZipRecruiter salary data. Most workers in this role earn between $22.60 and $29.09 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Graph Neural Network position, and why are they important?

To excel as a Graph Neural Network Engineer, you need a strong background in machine learning, graph theory, neural networks, and proficiency in programming languages such as Python. Familiarity with deep learning frameworks like PyTorch or TensorFlow, and experience with specialized libraries such as DGL or PyTorch Geometric are highly valued. Excellent problem-solving skills, teamwork, and the ability to communicate complex concepts to both technical and non-technical stakeholders will help you stand out. These combined abilities enable professionals to design, implement, and deploy cutting-edge GNN models that address complex, real-world data-structure challenges across various industries.

What does a typical project workflow look like for a Graph Neural Network Engineer?

A typical project workflow for a Graph Neural Network Engineer involves collaborating with data scientists and domain experts to understand the problem, preprocessing and visualizing graph-structured data, and selecting appropriate model architectures. The role often includes building, training, and evaluating GNN models, iterating on hyperparameters, and deploying models to production environments. Throughout the process, you will engage in code reviews, document findings, and present results to stakeholders. Teamwork and effective communication are essential, as projects frequently require close collaboration with researchers, software engineers, and business units to ensure solutions meet practical needs and performance goals.

What is a Graph Neural Network job?

A Graph Neural Network (GNN) job typically involves designing, implementing, and optimizing neural network models that operate on graph-structured data. Professionals in this role apply GNNs to tasks like recommendation systems, fraud detection, social network analysis, and molecular property prediction. Responsibilities often include data preprocessing, model architecture selection, training, evaluation, and deployment. Strong knowledge of machine learning, deep learning frameworks (such as PyTorch or TensorFlow), and graph theory is essential.

More about Graph Neural Network jobs
What cities are hiring for Graph Neural Network jobs? Cities with the most Graph Neural Network job openings:
What are the most commonly searched types of Graph Neural Network jobs? The most popular types of Graph Neural Network jobs are:
What states have the most Graph Neural Network jobs? States with the most job openings for Graph Neural Network jobs include:

Graph Machine Learning Engineer (Network)

Vailexa

Plano, TX โ€ข On-site, Remote

Full-time

Posted 6 days ago


Job description

Build More Than Just a Career. Build Your Future.

At Vailexa, we're not just hiring โ€” we're building thinkers, creators, and future leaders.

We believe in giving people the space to grow, the freedom to think, and the opportunity to create real impact from day one. If you're someone who wants to learn fast, take ownership, and grow beyond limits, you'll feel right at home here.

Summary: We are seeking a talented Graph Machine Learning Engineer to join our team and drive the development of innovative graph-based machine learning models. The ideal candidate will leverage their expertise to solve complex problems and enhance our data-driven decision-making capabilities.

Responsibilities:

  • Design and implement graph neural network models to extract insights from large datasets.
  • Collaborate with cross-functional teams to integrate graph machine learning solutions into existing systems.
  • Develop scalable algorithms for graph data processing and analysis.
  • Perform data pre-processing and feature engineering to ensure high-quality model inputs.
  • Stay up-to-date with the latest trends and advancements in graph machine learning.
  • Conduct experiments to evaluate model performance and refine algorithms as necessary.

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
  • Proven experience in machine learning, with a focus on graph-based methods.
  • Strong programming skills in Python and familiarity with libraries such as TensorFlow, PyTorch, or similar.
  • Knowledge of graph databases and query languages (e.g., Neo4j, Cypher).
  • Excellent problem-solving skills and the ability to work independently and collaboratively.
  • Strong communication skills to convey complex technical concepts to non-technical stakeholders.

Ready to take the next step?

If you're excited about this role and ready to grow with a team that values ambition, ideas, and impact โ€” we'd love to hear from you.

๐Ÿ‘‰ Apply now and start building your journey with Vailexa.