Block

Block is a company that consists of Square, Cash App, Spiral, TIDAL, TBD, and foundational teams. They are focused on economic empowerment by creating tools to expand access to the economy. Square helps sellers run and grow businesses, Cash App redefin...

Capital Markets

Financials

10K-50K (12428)

Founded 2009

61 open positions

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Staff Machine Learning Engineer, Underwriting and Credit

2 months, 2 weeks ago

United States, Canada

Full-time

Lead

Machine Learning Engineer

Software Development

Apache Airflow AWS GCP GitHub LightGBM LLM MLflow NumPy Pandas Prefect Python PyTorch Scikit-learn Snowflake SQL XGBoost

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Block

Capital Markets

10K-50K

Founded 2009

View All Jobs 61

Description

Build, evaluate, and maintain underwriting and decisioning models for Cash App Borrow and Afterpay.
Design and evolve credit decision frameworks, including modeling, automation, and policy logic that manage credit exposure over time.
Design and run experiments to measure model performance, approval rates, loss, and the impact of credit policy decisions.
Develop deep understanding of borrower behavior, repayment dynamics, and portfolio structure to inform model design and decision logic.
Work across the full modeling lifecycle, including problem formulation, feature engineering, training, calibration, deployment, monitoring, and iteration in production.
Contribute analysis that explains model behavior, tradeoffs, and uncertainty to senior technical and business leaders.
Build agentic engineering workflows that accelerate development, testing, documentation, and developer productivity.
Collaborate with Product, Engineering, Legal, Compliance, and Operations to align credit systems with business and regulatory requirements.
Share modeling context and approaches across teams to align how credit risk is measured, interpreted, and discussed.
Shape adoption of AI developer tooling by defining review practices, quality standards, and governance patterns.

Requirements

Bachelor's degree in a quantitative field such as Mathematics, Statistics, Physics, or Computer Science; advanced degrees are welcome.
10+ years of experience 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, including designing holdouts, measuring lift, and evaluating models beyond aggregate metrics.
Experience with model monitoring, degradation detection, and retraining strategies in production systems.
Proficiency with AI-native development workflows, including LLMs, agentic coding tools, and AI-assisted automation.
Experience explaining modeling concepts, results, and limitations to senior stakeholders and cross-functional partners.
Experience working across disciplines in environments with meaningful constraints.
Experience with Python and common ML libraries such as NumPy, Pandas, scikit-learn, PyTorch, XGBoost, and LightGBM.
Experience with tools and platforms such as MLflow, SQL/Snowflake, GitHub, GCP/AWS, Prefect, Airflow, internal feature stores, and model hosting platforms is helpful.

Benefits

Remote work for candidates based in the US or Canada.
Competitive market-based pay with a listed salary range of $276,800 to $415,200 USD depending on location and qualifications.
Medical insurance.
Flexible time off.
Retirement savings plans.
Modern family planning support.
Inclusive interview process with reasonable accommodations for disabled applicants.

Interested in this position?

Apply directly on the company website

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