Applied ML Graph Neural Network Research Software Engineer
Core
Design, train, and deploy Graph Neural Networks (GNNs) and graph embedding models to solve industrial temporal and relational data problems for Google's systems.
Role type
Applied ML Research Software Engineer (Graph Neural Networks)
Builds
GraphFlow GNN library and a unified GNN/AI agent system for monitoring and optimizing core infrastructure (storage, networking, compute).
Domain
Artificial Intelligence / Graph Machine Learning / Systems Infrastructure
Deliverable
production ML models
Required skills
Graph Neural Networks (GNNs), graph embedding models, PyTorch Geometric (PyG), JAX/Jraph, TF-GNN, ML infrastructure, model deployment, model evaluation, optimization, data processing, debugging
Preferred skills
Leading R&D and production of complex ML/Infra algorithms
Technologies
PyTorch Geometric, JAX, Jraph, TF-GNN
Responsibilities
Identify, develop, and productionize GNN/ML methods driven by client feedback, brainstorming, and original research; Develop and productionize industrial GNN/ML models and infrastructure for the GraphML for Google Systems initiative; Partner with product teams and research groups to translate business requirements into ML solutions.
