21 hours ago
Responsibilities
- Build and evolve a unified graph schema combining fraud and account data sources.
- Develop large-scale graph ingestion and feature pipelines using Databricks and Spark.
- Apply Graph Data Science algorithms for community detection, centrality analysis, and node embeddings.
- Develop graph machine-learning models, including Graph Neural Networks, and integrate risk signals into downstream ML workflows.
- Productionize scalable, reliable, observable graph systems and optimize query and inference performance.
- Own incremental refresh, supernode handling, monitoring, and cost efficiency for the graph platform.
- Contribute to pipeline orchestration, versioning, automated retraining, and production monitoring practices.
- Collaborate with data science, product, and platform teams and incorporate advances in graph ML and network science.
Requirements
- Bachelor’s or graduate degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent experience.
- At least 6 years of professional experience building and deploying data or machine-learning solutions at scale.
- Strong Python programming skills and extensive data-pipeline development experience with Databricks and Spark.
- Practical experience with graph platforms such as Neo4j, Amazon Neptune, TigerGraph, or Memgraph and the Graph Data Science library.
- Experience applying algorithms including PageRank, Louvain, Label Propagation, FastRP, or Node2Vec to network data.
- Knowledge of the full data and ML lifecycle, including ingestion, feature engineering, deployment, and monitoring.
- Strong understanding of data modeling, query optimization, and production system integration.
- Preferred experience with Graph Neural Networks, fraud or anomaly detection, behavioral modeling, managed graph databases, incremental graph refresh, and supernode management.
Benefits
- Adobe describes comprehensive benefits programs and an inclusive culture that empowers employees to make an impact.
- Adobe is an equal opportunity employer and provides accessibility accommodations during the recruiting process.
Tech Stack
Categories
Data EngineeringML Engineering
About Adobe
Adobe empowers everyone, everywhere to imagine, create, and bring any digital experience to life. From creators and students to small businesses, global enterprises, and nonprofit organizations — customers choose Adobe products to ideate, collaborate, be more productive, drive business growth, and build remarkable experiences.