Applied ML Graph Neural Network Research Software Engineer
RemoteFull-timePosted 2w ago
About the role
Applied ML Graph Neural Network Research Software Engineer position at Google, Zürich, Switzerland. Focuses on developing production-ready graph neural network (GNN) methods, deploying ML infrastructure, and collaborating with product teams to apply graph ML to industrial temporal and relational data problems within Google's systems.
Responsibilities
- Identify, develop and productionize GNN/ML methods driven by client feedback, team brainstorming, literature review and original research applied into the GraphFlow GNN library.
- Develop and productionize industrial GNN/ML models and infrastructure for the GraphML for Google Systems cross-Product Area initiative to build a unified GNN and AI agent system to support Google's Systems.
- Partner closely with product teams and research groups to translate business requirements into ML solutions.
Qualifications
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- Experience designing, training, and deploying Graph Neural Networks (GNNs) or graph embedding models using frameworks such as PyTorch Geometric (PyG), JAX/Jraph, or TF-GNN.
Skills
Required:ML infrastructureGraph Neural Networks (GNNs)
Last updated Oct 23, 2026. Interested? Apply on the company site.
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