DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!
We are hiring an AI/ML Engineer to serve as a technical architect for our Intelligence Layer and Data Consortium. This is a specialized engineering role—distinct from general web development—focused on building the high-scale "muscle" that powers our fraud intelligence. You will design and maintain distributed pipelines that ingest real-time signals from millions of users, and engineer backend systems that enable our Agentic Flow to "auto-tune" strategies. You will also play a key role in building agentic flows and AI applications using state-of-the-art, out-of-the-box large language models (LLMs) available on the market, in addition to helping build and deploy traditional machine learning models.
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DataVisor is the leading fraud detection company powered by transformational AI technology. Using proprietary machine learning algorithms, DataVisor restores trust in digital commerce by enabling organizations to proactively detect and act on fast...
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