Software Development Engineer 3 - Graph Engineering

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Skills you'll use

What you'll do

• Adobe is seeking a passionate engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide.
• In this role, you will compose and develop our unified graph along with the detection systems running on it. You will merge multiple isolated fraud graphs into one scalable source that identifies non-genuine and abusive signals across hundreds of millions of users. You will manage the entire lifecycle: starting from raw behavioral and account data, progressing through large-scale graph modeling and ingestion using Databricks and Spark, applying Graph Data Science algorithms and graph ML, and delivering production-ready detection for enforcement.
• This role is for an engineer eager to manage graph systems entirely, covering schema, pipelines, community detection, and graph ML rather than using pre-built solutions.

Who can apply

• Bachelor's degree or graduate degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field.
• 6+ years of professional experience building and deploying data or ML solutions at scale.
• Solid programming skills in Python, with practical experience developing extensive data pipelines on Databricks and Spark.
• Practical experience working with graph platforms such as Neo4j, Amazon Neptune, TigerGraph, or Memgraph, along with applying the Graph Data Science (GDS) library.
• Practical experience implementing GDS algorithms like PageRank, Louvain/Label Propagation for community detection, or Node Embeddings (FastRP, Node2Vec) to extract insights from network data.
• Comprehensive knowledge of the entire data and ML lifecycle, covering ingestion, feature engineering, deployment, and monitoring.
• Strong grasp of data modeling, query optimization, and production system integration.

About Adobe

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