Staff Machine Learning Engineer, Underwriting and Credit at Block · Lumi · Lumi

Responsibilities

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.
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.

Staff Machine Learning Engineer, Underwriting and Credit

Responsibilities

Qualification

Required

Benefits

Company

Block

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