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HOME AI & Research Senior Research Scientist, Graph Neural Network
  • Google
  • New York, NY
  • 8 days ago
  • $174,000–$252,000 / year
Google VERIFIED EMPLOYER

Senior Research Scientist, Graph Neural Network.

AI & Research
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Senior Research Scientist, Graph Neural Network: our view in 3 lines...

  • The Role:This role is for an experienced researcher who develops neural network methods for graph-structured data and large language models.
  • The Person:The person will invent novel neural architectures and graph encoders, author research papers, define data structures, frameworks, and evaluation metrics for research projects, and identify research gaps while collaborating with stakeholders.
  • Requirements:The ideal candidate holds a PhD in Computer Science or equivalent practical experience, has two years of experience leading a research agenda, and has worked with PyTorch, TensorFlow, Jax, and Ray.

About the role

Minimum qualifications:

  • PhD in Computer Science, a related field, or equivalent practical experience.
  • 2 years of experience leading a research agenda.
  • Experience with AI/ML technologies (e.g., frameworks for deep learning (PyTorch, TensorFlow, Jax, Ray), AI accelerators (TPUs, GPUs), model architectures (encoders, decoders, transformers), or using machine learning APIs).
  • One or more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications:

  • 1 year of experience leading research efforts and influencing other researchers.

About the job

As a Research Scientist on the Graph Neural Network (GNN) team within OMEGA, you will pioneer research at the intersection of deep learning, structured data, and Large Language Models (LLMs). In this role, you will invent novel neural architectures, graph encoders, and agentic retrieval methods that bring relational reasoning to foundation models at massive scale. You will collaborate closely with partners across Google Research, Google DeepMind, and core product teams to translate theoretical breakthroughs into production-grade frameworks and next-generation AI capabilities.

As a part of the Graph Neural Network (GNN) team, you will bridge relational structure and deep learning, making it seamless to integrate graph-structured data into neural networks and foundation models at massive scale. As a part of the team, you will conduct fundamental research and build production-grade frameworks to train and deploy these models over complex, heterogeneous graphs. Recently, the team's work has expanded into generative AI, developing structured data encoders, graph tokens, hybrid graph-sequence architectures, and graph-based retrieval and agentic systems to enhance Large Language Models (LLMs).

Google Research is building the next-generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Author research papers to share and generate impact of research results across function and in the research community.
  • Help in growing research business by sharing research trends and best practices within the community.
  • Drive project work by defining the data structure, framework, design, and evaluation metrics for research solution development and implementation. Identify timelines and obtain resources needed.
  • Discover new and upcoming research areas by interacting with potential external and internal collaborators, helping to develop long-term research strategies and plans to expand the impact of Google research.
  • Identify defined problems/gaps in existing technology and engage stakeholders and leaders to address them.
Published October 27, 2026
Location New York, NY
Category AI & Research  

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