Machine Learning Engineer

Block builds technology to increase access to the global economy. Across our ecosystem, including Square and Cash App, we create tools that help businesses run and grow, and individuals move, manage, and grow their money with confidence. Square empowers sellers of all sizes with integrated, omnichannel tools to accept payments, manage operations, access financial services, and reach customers across online and in-person channels. Cash App complements this by providing a fast, accessible financial platform for millions of people to send, spend, save, invest, and borrow, helping redefine how individuals interact with money.Operating at massive scale across both ecosystems means trust and safety are foundational. Our teams build systems that protect real people and businesses, safeguard financial activity, and ensure our products remain reliable, secure, and easy to use. Block is a global, distributed company with a culture rooted in ownership, creativity, and impact. Whether supporting sellers on Square or customers on Cash App, we’re united by a shared mission: to make the global economy more accessible and inclusive. The Role Block has provided over $200 billion in credit to customers globally. Afterpay and Cash App Borrow are our two largest products in this space, expanding access to credit for consumers who are often underserved by traditional financial systems. Machine learning is the core of how these products work. Our models decide who gets credit, how much, and under what terms. They underwrite customers across a wide range of credit profiles, including many with thin or no traditional credit history. The modeling challenges are real: maintaining calibration across diverse borrower populations, designing features that generalize as the portfolio grows, and balancing approval rates against loss performance at every decision point. This requires strong fundamentals, disciplined experimentation, and continuous evaluation in production. On the Credit Modeling team, you will be a senior individual contributor building and evolving the ML systems behind these products. You will work across the full modeling lifecycle: problem formulation, feature development, training, calibration, experimentation, deployment, monitoring, and iteration. You will operate across one of these lending products with different borrower populations, repayment structures, and regulatory surfaces. We use agentic engineering and AI tooling to build reliable, high-velocity workflows that enable this work. That includes code generation, automated testing, documentation, and developer tooling. You will help define how these practices scale across the team in ways that are rigorous, auditable, and trusted. This is a team that values high output and rigor. We move fast, we test carefully, and we hold our work to a high standard because the models we build determine real credit outcomes for real people. This role is fully remote for candidates based in the US or Canada. You Will Build, evaluate, and maintain underwriting and decisioning models across Cash App Borrow and Afterpay. Design and evolve credit decision frameworks, including the modeling, automation, and policy logic that manage credit exposure over time. Design and run experiments to evaluate model performance, measure impact on approval rates and loss, and inform credit policy decisions. Develop deep understanding of borrower behavior, repayment dynamics, and portfolio structure across both products, and use that to inform model design and decision logic. Contribute analysis and perspective that inform portfolio-level decisions, including explaining model behavior, tradeoffs, and uncertainty to senior technical and business leaders. Work across the full modeling lifecycle: problem formulation, feature engineering, training, calibration, deployment, monitoring, and iteration in production. Build agentic engineering workflows that accelerate development, testing, and documentation. Collaborate with Product, Engineering, Legal, Compliance, and Operations to ensure credit systems reflect business goals and regulatory expectations. Share modeling context and approaches across teams, helping align how credit risk is measured, interpreted, and discussed. Shape how AI developer tooling is adopted across the team, defining review practices, quality standards, and governance patterns. You Have A Bachelor's degree in a quantitative field (e.g., Mathematics, Statistics, Physics, Computer Science). Advanced degrees welcome. 10+ years applying AI, machine learning, or statistical modeling in decisioning contexts such as credit, risk, fraud, recommendations, or similar domains. Experience with probabilistic models and decision systems, including calibration, score transformations, and interpretation of model outputs. Strong experimentation skills: you know how to design holdouts, measure lift, and evaluate models beyond aggregate metrics. Experience with model monitoring, degradation detection, and retraining strategies in production systems. Proficiency with AI-native development workflows. You use LLMs, agentic coding tools, and AI-assisted automation as a regular part of how you build and ship. Experience explaining modeling concepts, results, and limitations to senior stakeholders and cross-functional partners. Experience working across disciplines in environments with meaningful constraints. Technologies We Use and Teach Python (NumPy, Pandas, scikit-learn, PyTorch, XGBoost, LightGBM) AI development tools as core infrastructure: Claude Code, Cursor, Copilot MLflow for experiment tracking and model registry Internal feature store and model hosting platform Prefect and Airflow for orchestration SQL / Snowflake GitHub GCP / AWS We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page . Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future. To find a location’s zone designation, please refer to this resource . If a location of interest is not listed, please speak with a recruiter for additional information. Zone A: $276,800 — $415,200 USD Zone B: $276,800 — $415,200 USD Zone C: $276,800 — $415,200 USD Zone D: $276,800 — $415,200 USD