Staff Machine Learning Engineer, Credit Products (Square Financial Services)
AI summary of the role
This is a Staff-level ML Engineer role on the Credit and Lending team within Square Financial Services, a regulated bank subsidiary of Block.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Apply rigorous scientific methods to underwrite new customer segments using alternative data sources and advanced architectures.
- Lead ML Operations and Infrastructure initiatives to scale data ingestion and enable complex neural networks.
- Design and implement the full credit modeling stack, owning the lifecycle of credit decisioning in production.
- Use data science to leverage new data sources, making sense of messy datasets and informing business decisions.
What you’ll bring
- Minimum 8 years experience with Bachelor's, 6 years with Master's, or PhD with 3 years, focused on production ML/statistical models.
- Degree in a technical field (Computer Science, Mathematics, Statistics, Physics, Engineering) with preference for advanced degree or research track record.
- Strong quantitative intuition and data visualization skills for sophisticated ad-hoc analysis.
- Full-stack proficiency preferred, from data pipelines to production-grade software architecture.
Technologies
machine learning · statistical modeling · gradient boosting · tree-based models · neural networks · data pipelines · ML operations · credit modeling · underwriting
About Block (Square)
Multi-ecosystem fintech: Square (SMB commerce + payments), Cash App (consumer banking), Afterpay (BNPL), Tidal (music), TBD/Spiral (Bitcoin infra).
Public
Source and classification
Internal deployment & tooling · Evidence for this classification:
underserved by the traditional financial system. As a Machine Learning Engineer within Square Financial Services (SFS), you will occupy a high-leverage role at the intersection of regulated banking and advanced autonomous systems. This position requires full-stack ownership of the credit engine, from the curation of novel data signals to the implementation of the decisioning logic that drives Block’s top-line growth. Our credit products are material drivers of the company’s profitability and are frequently highlighted in executive reviews and quarterly earnings reports. We are seeking a scientifically-minded contributor capable of delivering extraordinary individual leverage to expand our underwriting capabilities into previously untapped segments through pragmatic policy evolution and advanced modeling techniques. You Will Apply a rigorous scientific mindset to the challenge of
More from the job description
Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block. The Role The Credit and Lending team is responsible for the predictive intelligence that underpins Block’s primary capital-intensive products. These products unlock unique access to credit for our customers, many of whom are otherwise underbanked and underserved by the traditional financial system. As a Machine Learning Engineer within Square Financial Services (SFS), you will occupy a high-leverage role at the intersection of regulated banking and advanced autonomous systems. This position requires full-stack ownership of the credit engine, from the curation of novel data signals to the implementation of the decisioning logic that drives Block’s top-line growth. Our credit products are material drivers of the company’s profitability and are freq [... source excerpt omitted ...] g extraordinary individual leverage to expand our underwriting capabilities into previously untapped segments through pragmatic policy evolution and advanced modeling techniques. You Will Apply a rigorous scientific mindset to the challenge of underwriting new customer segments, involving the evaluation of alternative external data sources and the deployment of advanced architectures to enhance predictive accuracy. Lead complex ML Operations and Infrastructure initiatives that advance our modeling capabilities, such as scaling data ingestion or enabling the use of more complex neural networks. Design and implement the full credit modeling stack, taking responsibility for the [... source excerpt omitted ...] entify and execute material improvements to credit policy, applying an analytical lens to determine where technical or logic shifts can yield significant positive outcomes for the customer and the bank’s portfolio. Support team members in ad-hoc and scheduled updates to existing models, and help troubleshoot issues in a real-time production environment. Operate effectively within the framework of a regulated bank (SFS), balancing rapid innovation with the requirements of safety, soundness, and compliance. You Have Minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience, with a focus on developing an
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