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 [https://www.google.com/about/careers/applications/benefits/].
across function and in the research community.
practices within the community.
evaluation metrics for research solution development and implementation. Identify timelines and obtain resources needed.
external and internal collaborators, helping to develop long-term research strategies and plans to expand the impact of Google research.
and leaders to address them.
(PyTorch, TensorFlow, Jax, Ray), AI accelerators (TPUs, GPUs), model architectures (encoders, decoders, transformers), or using machine learning APIs).
or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
researchers.
GoogleBengaluru, Karnataka, India
Pay not posted
Posted 15 days ago
checked 4 days agoNVIDIAIndia, Bengaluru +2
Pay not posted
Posted 21 days ago
checked 4 days agoNVIDIAUS, WA, Remote +2
$192K–$357K / yr
Posted 15 days ago
checked 4 days agoGoogleBengaluru, Karnataka, India
Pay not posted
Posted 9 days ago
checked 4 days agoGoogleBengaluru, Karnataka, India
Pay not posted
Posted 26 days ago
checked 4 days agoGoogleBengaluru, Karnataka, India
Pay not posted
Posted 10 days ago
checked 4 days agoSource: the company job board. We last checked this job 8 days ago. We first saw it 8 days ago. A job on a job board does not always mean that the team interviews people now.
See total pay at Google on Levels.fyiBase, stock and bonus, as employees report it.
No one has reported an interview at Google yet. Did you interview there? Add the questions.
This base pay is below the median for senior AI research jobs in the Bay Area.
We compare the middle of each posted range. This is base pay as posted. The group does not include this job.