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We are seeking a Staff Software Engineer with deep expertise in graph theory, graph-based systems, and large-scale social graph infrastructure. In this role, you will serve as a technical leader driving the architecture, implementation, and scaling of our social graph platform—powering trust, recommendations, user discovery, and other core product experiences. You will collaborate closely with Data Science, ML, Product, and Infrastructure teams to design graph representations, build ingestion and transformation pipelines, and deploy graph-backed models at massive scale. You will set technical direction for how we leverage connectivity, influence, and reputation signals to improve safety, personalization, and engagement across our ecosystem.
Job Responsibility:
Serve as the technical lead for initiatives related to social graph modeling, storage, retrieval, and computation
Architect and scale graph databases and graph query systems capable of supporting billions of nodes and edges with low-latency performance
Design and ship pipelines for ingesting, cleaning, and transforming social and behavioral data into graph structures
Partner with ML teams to productionize graph-based features, including embeddings, similarity signals, trust metrics, and GNN-powered ranking features
Lead the development of graph-informed recommendation, trust, and safety systems, ensuring models reflect real-world connectivity patterns
Define and implement feature engineering strategies leveraging graph topology (e.g., mutual connections, influence scoring, community structure)
Contribute to architecture decisions related to streaming systems (Kafka, Flink, Spark Streaming) and real-time graph updates
Mentor engineers and guide best practices on graph design, distributed systems, feature computation, and ML integration
Collaborate with Product to translate graph capabilities into business-impacting features that drive trust, engagement, and discovery
Ensure reliability, scalability, observability, and data quality in all graph-related systems
Requirements:
8+ years of industry experience, including significant experience at senior / staff / principal levels
Demonstrated expertise launching and scaling graph-based applications in production
Deep understanding of graph theory, graph algorithms (e.g., traversal, clustering, centrality), and modern graph data structures
Expert-level experience with graph databases (Neo4j, TigerGraph, JanusGraph, DGL-backed systems, etc.) and efficient graph querying
Proven ability to design high-scale pipelines for ingesting and transforming social or behavioral data
Experience with distributed streaming frameworks (Kafka, Flink, Spark Streaming)
Hands-on experience incorporating graph-derived features into recommendation, ranking, trust, or safety models
Familiarity with Graph Neural Networks (GNNs), graph embeddings, or graph-based ranking systems
Strong product intuition and ability to articulate how graph systems drive business outcomes
Ability to influence architectural direction and mentor teams
Nice to have:
Experience supporting real-time or near-real-time graph updates
Background in large social networks, marketplaces, trust & safety, or other graph-heavy domains
Track record of cross-functional technical leadership
Publications, patents, or open-source contributions in graph algorithms, GNNs, or infrastructure
What we offer:
Competitive pay and comprehensive healthcare benefits
Financial assistance for things like hybrid work, family planning