Overview
Head of Machine Learning for Tide’s Ongoing Monitoring team, responsible for leading risk engineering and ML-driven fraud and risk management capabilities at scale.
What you'll do
- Define and execute a risk engineering strategy aligned to long-term vision.
- Lead engineering managers and engineers to drive excellence and collaboration.
- Architect and scale risk infrastructure for real-time decision-making and fraud prevention.
- Develop self-service risk tooling for product, compliance, and risk operations teams.
- Collaborate with legal and compliance experts to support regulatory compliance.
- Lead data- and machine-learning initiatives for fraud detection and compliance insights and automation.
What you'll need
- 12+ years of engineering experience with at least 2 years in a senior leadership role.
- Deep experience in fraud prevention and compliance (KYC/KYB, AML).
- Strong experience with supervised/unsupervised ML models, decision trees, neural networks, and LLMs.
- Hands-on experience with multi-agent orchestration frameworks such as LangGraph or AutoGen.
- Experience with fraud vectors and AML typologies.
- Track record detecting deepfakes, synthetic identities, and prompt injection attacks on financial systems.
- Minimum 3+ years building and deploying production-grade risk-scoring environments at scale.
Details
- Team: Ongoing Monitoring, within Tide’s trust and safety ecosystem.
- Working model: flexible workplace with in-person and remote work supported.
Read the full description and apply on the company’s own careers page.
