Real-time fraud and AML risk platform for fintechs and payments
Sardine builds fraud detection and AML tooling on a GCP-native streaming stack (Pub/Sub, Apache Beam, Flink, BigQuery) feeding gradient-boosted and PyTorch models via Vertex AI and Kubeflow. Its project list centers on a Chronon feature platform, sanctions entity matching and KYC onboarding models. Hiring is accelerating, senior-weighted and spread across ten countries, with a CISO search and Datadog observability and FinOps work pointing to scaling pains.
Notable leadership hires: Chief Information Security Officer
Sardine, founded in 2020 and headquartered in San Francisco, sells a risk platform that combines fraud prevention and anti-money laundering capabilities. Its coverage spans device fingerprinting, behavioral biometrics, payment and chargeback fraud, transaction monitoring and case management. Customers are financial services, payments and digital businesses that need to stop fraud as it happens and run compliance operations more efficiently. The privately held company employs 201–500 people and recruits across North America, Latin America, Europe, the Middle East and Asia-Pacific.
Sardine runs on GCP with BigQuery, Pub/Sub, Apache Beam, Flink, Spark and Airflow, builds models with PyTorch, XGBoost, LightGBM and Vertex AI, and codes in Python, Go and Ruby on Docker and Kubernetes.
Job posts point to a Chronon feature platform, a sanctions entity matcher, KYC onboarding models, scaling ML fraud models into production, Datadog observability improvements and FinOps governance.
Sardine hires in the United States, Mexico, the UAE, Brazil, Bulgaria, Canada, Singapore, Germany, Ireland and Australia, with engineering and sales leading the mix.
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Sardine's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.