Senior Graph ML Scientist: Entity Resolution for Fraud

TWG AI; New York (NY); On-site; USD 190,000 - 290,000; Full time

Benefits offered by this job

Bonus

Medical benefits

Onsite office

Job summary

TWG AI in New York, NY is seeking a senior ML engineer focused on graph-based fraud detection and entity resolution. You will own the graph and decoding of identities, turning financial and on-chain data into actionable networks to detect collusive rings and coordinated activity.

The role is onsite at our NY offices with a base pay of $190,000-$290,000 plus bonus and full benefits. You will collaborate with management and engineering to scale graph pipelines, improve detection, and advance

Qualifications

• Strong applied graph ML experience: graph representation learning, embeddings, and/or GNNs on large-scale graphs.
• Entity resolution / record linkage at scale, ideally with cluster stability over time.
• Community and cluster detection, both embedding-based and classical approaches.
• A track record detecting coordinated or collusive behavior — fraud, AML, or coordinated-campaign work all translate well.
• Production ML experience: you've built graph pipelines that run, not just research notebooks.

Responsibilities

• Build and maintain the entity graph that links accounts, counterparties, wallets, and behavior into a single picture of who is really acting
• Develop entity-resolution and clustering methods that stay stable over time, so the same actor is recognized as they resurface
• Detect coordinated behavior and collusion rings — including cases with no explicit shared identity; on the DeFi side, wallet-farming and sybil detection as direct outputs of entity resolution
• (DeFi seat) Co-own the Attribution Substrate: fusing vendor attribution clusters (e.g., Chainalysis) with on-chain behavioral clustering into a confidence-scored entity-resolution layer
• Build graph-based features and representations (embeddings, network features) that feed the wider detection system
• Partner with engineering as the graph extends to new data sources and market types

Skills

Graph ML

Entity resolution

Fraud detection

Production ML

Financial crime exposure

Job description

TWG AI in New York, NY is seeking a senior ML engineer focused on graph-based fraud detection and entity resolution. You will own the graph and decoding of identities, turning financial and on-chain data into actionable networks to detect collusive rings and coordinated activity.

The role is onsite at our NY offices with a base pay of $190,000-$290,000 plus bonus and full benefits. You will collaborate with management and engineering to scale graph pipelines, improve detection, and advance