Lead Machine Learning Scientist - Graph Representation

About the opportunity

Pioneer large-scale Graph Neural Networks (GNNs) modeling entity relations, academic citations, and enterprise knowledge.

What you will do

• check_circle Lead fundamental research in Graph Neural Network architectures, scalable sub-graph sampling, and hypergraph representations.
• check_circle Collaborate with product teams to deploy graph embeddings into search, maps, and Google Cloud services.
• check_circle Publish landmark papers at top-tier ML conferences (NeurIPS, ICML, ICLR, KDD).
• check_circle Advise internal research scientists and external academic partners on graph deep learning.

What we are looking for

• arrow_circle_right PhD in Computer Science, Machine Learning, or related field with significant peer-reviewed publication record.
• arrow_circle_right 6+ years hands-on experience developing advanced deep learning algorithms.
• arrow_circle_right Recognized technical leadership in Graph Neural Networks, PyTorch Geometric, or DGL.

Skills & Tech Stack