Staff Machine Learning Engineer - Risk

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do • Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. • Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. • Design and productionize models rather than just prototype them, including training pipelines, retraining cadence, drift monitoring, and deployment. • Develop reliable, automated, and reproducible ML workflows across the full model lifecycle. • Set technical standards for how ML gets built and shipped on the risk team, including architecture and technical direction. • Own the operational health of models in production, from low-latency inference to monitoring and incident response. • Help shape the future of risk and ML at Breeze. What We're Looking For • 8+ years in ML engineering, with real production ownership rather than research or modeling alone. • A track record building risk or fraud-adjacent ML systems, ideally in payments or fintech. • Experience with real-time payment-risk systems, including low-latency model inference, monitoring, and incident response. • A strong collaborator across engineering and data engineering - this role sits at that intersection. • Comfortable being the senior technical voice on a small team, with cross-functional technical leadership, able to set direction and not just execute. • Comfortable operating in fast-moving environments without an established playbook. • A builder mentality with a strong bias toward action. • Excited to use AI and automation to work smarter and rethink existing processes. • Comfortable getting into the details and doing the work, regardless of seniority. Nice to Have • Familiarity with payments-specific risk signals such as chargebacks, dispute networks, and tokenization context. • Experience establishing ML platform standards and operating models in a growing organization. • Experience at an early-stage or high-growth startup. Why Join Breeze Make an outsized impact: We're successful and still early, with meaningful traction and strong financial foundations. Lean teams, few layers, and direct access to decision-makers mean you'll have real ownership and the autonomy to make things happen. Solve hard, meaningful problems: Work at the intersection of AI, payments, stablecoins, risk, compliance, financial infrastructure, and global commerce as we build an intelligent infrastructure layer that goes far beyond payments. Build AI-first: AI isn't an add-on. It's central to how we're building our products and how our teams operate. You'll experiment with new tools, automate the repetitive, and continuously rethink how to work smarter. Work with an exceptional team: Join ambitious, curious, low-ego people who move quickly, hold a high bar, and care deeply about what they build. Grow with Breeze: As Breeze grows, strong performers can quickly expand their scope and take on bigger problems. Build for the long term: Backed by Sequoia Capital, Multicoin Capital, and The Chainsmokers, we're exceptionally well-capitalized with the runway to think big. In-Office Expectations Employees based in our New York City, NY office follow a hybrid work model and are expected to work from the office three days per week . Employees based in our Singapore office are expected to #J-18808-Ljbffr