> Markdown version of [/jobs/ext/2057932-staff-machine-learning-engineer-underwriting-and-credit](https://www.wearedevelopers.com/jobs/ext/2057932-staff-machine-learning-engineer-underwriting-and-credit). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Machine Learning Engineer, Underwriting and Credit - **Company:** Afterpay - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $276,800.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Automation of Tests, Mobile Application Development, Code Generation, Cursor (Graphical User Interface Elements), Programming Tools, Github, Machine Learning, SQL Databases, Google Cloud, Feature Engineering, Large Language Models, Snowflake, Information Technology, Machine Learning Operations - **Published:** August 14, 2026 - **Apply:** https://www.dice.com/job-detail/c2827b61-3ec0-4991-952f-7673484156ef ## About the Role * 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. ## Description 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., * 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 * Google Cloud Platform / 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 ., We may use automated AI tools to evaluate job applications for efficiency and consistency. These tools comply with local regulations, including bias audits, and we handle all personal data in accordance with state and local privacy laws. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Intelligent Automation using Machine Learning](https://www.wearedevelopers.com/videos/157-intelligent-automation-using-machine-learning) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)