Senior Research Scientist, Graph Neural Network
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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.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.
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