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Tide is a fintech platform serving over 2 million SMEs globally with business banking, invoicing, and accounting solutions. The Ongoing Monitoring team sits at the core of Tide's trust and safety ecosystem, building systems for fraud detection, financial risk management, and regulatory compliance.
As Head of Machine Learning, you will lead the engineering strategy and execution for risk and compliance systems. You'll manage a team of talented engineers and managers, fostering a culture of excellence and innovation. Key responsibilities include:
• Define and execute a risk engineering strategy aligned with Tide's long-term vision to support rapid, compliant growth
• Lead and grow a team of managers and engineers, building a culture of excellence and collaboration
• Build and scale risk infrastructure for real-time decision-making, data management, and fraud prevention
• Develop self-service tools for product, compliance, and risk operations teams to reduce dependencies
• Collaborate with legal and compliance to maintain regulatory leadership
• Champion data-driven risk management using machine learning for fraud detection and compliance
You bring 12+ years of engineering experience with at least 2 years in senior leadership (head, director, or senior manager), ideally in fintech or regulated tech. Deep expertise required in fraud prevention, KYC/KYB, and AML compliance. Strong technical background in supervised/unsupervised ML, decision trees, neural networks, and LLMs. Hands-on experience with multi-agent orchestration frameworks (LangGraph, AutoGen) for compliance workflows. Minimum 3+ years building production-grade risk-scoring systems at scale. Proven track record detecting deepfakes, synthetic identities, and prompt injection attacks. Solid foundation in cloud-native architectures, microservices, event-driven systems, and data platforms (AWS/GCP). Excellent people leadership skills.
