Staff Machine Learning Engineer, Credit Products
Block, Inc. is a technology company building tools for economic empowerment, operating a portfolio of financial brands including Square, Cash App, Afterpay, TIDAL, Bitkey, and Proto. It serves sellers, consumers, artists, and bitcoin users through payments, banking, buy-now-pay-later, music streaming, and bitcoin self-custody and mining products.
Maintainer signals as of 8/23/2026
Projects
About Block, Inc.
Block, Inc. builds technology aimed at increasing access to the global economy. Its brands each unlock different aspects of the economy: Square makes commerce and financial services accessible to sellers; Cash App is an easy way to spend, send, and store money; Afterpay (Clearpay in the UK) helps customers manage spending over time; TIDAL is a music platform empowering artists as entrepreneurs; Bitkey is a self-custody bitcoin wallet; and Proto builds open, accessible bitcoin mining hardware and services. Block has been a long-time advocate for bitcoin, integrating bitcoin buying/selling and Lightning Network payments into Cash App and Square, funding open-source bitcoin infrastructure through Spiral (including the Lightning Development Kit), and engaging in bitcoin policy advocacy through groups like COPA, the Digital Energy Council, the Crypto Council for Innovation, and the Texas Blockchain Council. The company also runs a significant open source program (contributing to projects like Goose, an on-machine AI developer agent, OkHttp, Retrofit, gRPC, Envoy, and MySQL) and an AI research effort, including co-founding the Agentic AI Foundation with Anthropic and OpenAI. Block serves individual consumers, small and medium-sized businesses/merchants, artists, and developers.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Own the full credit modeling stack from data ingestion through production decisioning. Evaluate alternative external data signals, apply rigorous scientific methods to underwrite new customer segments, deploy models into production, scale data pipelines and MLOps infrastructure, troubleshoot real-time model issues, and improve credit policy while balancing innovation with regulatory and compliance requirements.
Requirements
- At least 8 years of related experience with a Bachelor's degree, 6 years with a Master's degree, or 3 years with a PhD, focused on developing and deploying machine learning and statistical models in production
- Degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or another technical field
- Strong quantitative intuition and data visualization skills
- Full-stack proficiency across data pipelines and production-grade software architecture
- Ability to communicate clearly with technical and non-technical audiences
- Pragmatic problem-solving skills balancing business, technical, and regulatory constraints
- Familiarity with tree-based models and gradient boosting is helpful but not required
Responsibilities
- Underwrite new customer segments using rigorous scientific methods
- Lead ML operations and infrastructure initiatives
- Design and implement the full credit modeling stack
- Leverage new data sources for modeling using data science techniques
- Identify and execute material improvements to credit policy
- Support model updates and troubleshoot production issues
- Operate within regulated banking constraints balancing innovation and compliance
Benefits
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning