Senior Machine Learning Engineering Manager - Risk and Fraud

While many roles at Coinbase are remote-first, we are not remote-only. In-person participation is required throughout the year. Team and company-wide offsites are held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and fully supported.

About the Role

Coinbase's Risk AI/ML team is on a mission to make Coinbase the most trusted and easy-to-use platform in crypto. We build the sophisticated, scalable, and blockchain-aware ML systems that protect our customers from fraud, account takeovers (ATO), and scams. Our work is a core enabler for the business, allowing us to safely offer products like instant withdrawals, guest checkout, and new payment methods.

We are looking for a seasoned AI/ML leader to manage and scale our Risk AI/ML organization. In this high-impact role, you will be responsible for setting the strategic vision, leading multiple teams of managers and engineers, and owning the end-to-end ML systems that manage risk across Coinbase. This is a critical leadership position that partners directly with senior leaders in product, engineering, and operations to protect our users and the business.

What You’ll Be Doing (Job Duties)

• Lead and Scale: Lead, manage, and scale the Risk AI/ML organization, fostering a culture of technical excellence and rapid execution.
• Set Strategic Vision: Define and execute the multi-year technical and strategic roadmap for Risk AI/ML, identifying new threats and opportunities in the crypto ecosystem.
• Manage Through Others: Directly manage and mentor other ML managers and senior technical leads, growing their careers and impact.
• Drive Execution: Guide a 25+ person organization to design, build, and deploy the next generation of risk models (e.g., for Scams, ATO, Payments, and On-Chain Fraud) that have a direct, measurable impact on business goals.
• Own the System: Take full ownership of the end-to-end ML systems for Risk, from feature engineering and model development to live production monitoring and performance.
• Senior Stakeholder Management: Serve as the primary AI/ML voice for the Risk domain, collaborating with VPs and Directors in Product, Engineering, and Operations to turn complex business problems into a tangible ML roadmap.
• Hire and Develop Talent: Work with our talent organization to attract, hire, and retain top-tier ML managers and engineers.

What We Look For In You (Must Haves)

• Senior Management Experience: 10+ years of working experience in machine learning and 5+ years of ML/engineering management experience, with at least 2 years of experience managing other managers (managing through others).
• Deep Risk Domain Expertise: Proven experience and deep domain knowledge in the Risk, Fraud or Trust & Safety space. You have a track record of building ML systems to combat adversarial behavior (e.g., fraud, scams, account takeover, payment risk).
• Strategic Leadership: Experience setting a multi-quarter strategic roadmap for multiple ML teams and interfacing with senior-level (VP/Director) partners to drive business outcomes.
• Technical Credibility: Strong technical background in modern machine learning techniques and platforms (e.g., supervised/unsupervised learning, deep learning, MLOps, and common ML platforms like Tensorflow/PyTorch).
• Hiring & Team Building: A strong track record of hiring and developing top-performing ML managers and engineers.
• Execution Focus: An execution-focused mindset with a proven ability to navigate ambiguity, break down complex problems, and lead a large organization to deliver results.
• Strong Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical senior audiences.

Nice To Haves

• Previous experience in FinTech or Crypto.
• Experience applying advanced ML techniques to risk problems (e.g., Graph Neural Networks (GNNs), Transformers, LLMs, anomaly detection).
• Deep expertise with high-performance ML serving and MLOps platforms