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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Senior Machine Learning Engineer, Model Risk Management

2 months, 2 weeks ago

United States

Full-time

Senior

Machine Learning Engineer

Software Development

AWS Databricks GCP GitHub JIRA LightGBM Linear LLM MLflow NumPy Pandas Prefect Pytest Python PyTorch Scikit-learn Snowflake SQL XGBoost

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Block

Capital Markets

10K-50K

Founded 2009

View All Jobs 61

Description

Independently challenge model owners across lending, fraud, and AML by reproducing results, setting acceptance thresholds, and deciding whether models are sound.
Identify silent model errors, validate them before production, and evaluate models under rare events, shifting populations, and post-launch drift.
Work hands-on in unfamiliar codebases, learn the underlying data and conventions, and ship production code for validation tooling.
Build and improve agentic validation tooling, including orchestrating agents that run in parallel.
Reason about ML systems end to end, including features, training, serving, monitoring, and scale, to evaluate and challenge model designs.
Tie explainability and fair-lending findings on consumer credit models back to model and product decisions.
Help define how Block validates frontier production AI systems and establish standards where none exist yet.
Partner with Legal, Compliance, fair-lending, auditors, and bank partners on analysis and regulatory engagements.
Scope under-specified work into defensible validation plans and defend tradeoffs to model builders and senior stakeholders.

Requirements

Quantitative degree or equivalent experience.
Senior individual-contributor experience building or validating models in a high-stakes domain such as credit, fraud, or financial crime.
Strong effective-challenge methodology, including reproduction, conceptual-soundness review, benchmarking, stress testing, and outcomes analysis.
Deep applied ML and statistics across regression, tree ensembles, and deep learning, with strong judgment on evaluation, calibration, and generalization.
Experience with experimentation and statistical rigor, including holdout and experiment design and reasoning about uncertainty.
Production-quality Python, SQL on large datasets, and reproducible, tested code.
Fluency with modern AI tools, including building with LLMs and agentic systems, plus judgment about when their output can be trusted.
Familiarity with model risk management frameworks and fair-lending standards, with specifics learnable on the job.
Strong communication skills for explaining and defending conclusions to model owners and senior stakeholders.
Remote-friendly within approved U.S. locations.
Experience with technologies used by the team, including Python libraries such as NumPy, Pandas, scikit-learn, LightGBM, XGBoost, and PyTorch, is relevant.
Experience with MLflow, Databricks, Prefect, GCP Vertex AI, Snowflake, GitHub, CI, GCP, or AWS is a plus.

Benefits

Remote work within approved U.S. locations.
Medical insurance.
Flexible time off.
Retirement savings plans.
Modern family planning benefits.
Market-based pay with location-based salary zones.
Starting salary range of $189,000–$283,600 USD in Zone A.
Starting salary range of $179,600–$269,400 USD in Zone B.
Starting salary range of $170,100–$255,100 USD in Zone C.
Starting salary range of $160,700–$241,100 USD in Zone D.

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