As a Senior Machine Learning Engineer in Model Risk Management you will evaluate and validate models that assess risk in lending and fraud ensuring their robustness and reliability. You will collaborate with model owners tackle model challenges and build evaluation tools critical for understanding model performance.

Block builds simple powerful tools that make progress towards an economy that's truly open to all. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend send and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together we're helping build a financial system that is open to everyone. Join us.
The Role
Block lends moves money and screens for financial crime at enormous scale and one bad model can mean millions in credit losses suspicious activity that goes unreported or a fair lending violation. Model Risk Management is the independent function that decides whether a model is sound enough to put in front of customers and regulators.
The failures that matter rarely announce themselves: a model can clear every headline metric and still be broken underneath. It can pass clean at launch and then quietly drift as the population shifts until the loss it was supposed to prevent surfaces months later. The hard part is finding what looks right and is wrong then proving it well enough to hold up under questioning. Much of the work arrives under-specified so you scope it into a defensible plan ask the questions that surface the real requirements and defend your tradeoffs to the people who built the model you are challenging.
The same scrutiny you apply to models applies to AI. We build the tooling that lets a lean team validate at scale so you critically evaluate what it produces and own the evaluation that confirms its output is reliable enough to act on. That work matters most for the GenAI and agentic systems most teams have not figured out how to oversee yet.
As a senior individual contributor you lead through technical depth and cross-team scope and you partner widely across the organization. You work with the first-line modelers you challenge the Legal Compliance and fair-lending teams who rely on your analysis and the auditors and bank partners who carry it into regulatory engagements. This role is remote-friendly within approved US locations.
You Will

• Independently challenge model owners across lending fraud and AML: reproduce their results set and defend the acceptance thresholds and own the call on whether a model is sound.
• Hunt the silent errors that make metrics lie and prove them out before they reach production.
• Choose evaluation that holds up under real conditions: rare events shifting populations and drift that only shows up after launch.
• Work hands-on in codebases you did not write learning the data configs and conventions and ship production code in the tooling you build to validate them.
• Build the agentic validation tooling the team depends on orchestrating agents that run in parallel.
• Reason about ML systems end to end - how features training serving monitoring and scale fit together - to evaluate and challenge an owner's design.
• Tie explainability and fair-lending findings on consumer credit models back to the model and product decisions that follow.
• Help define how Block validates the systems at the frontier of production AI setting standards where none exist yet.

You Have

• A quantitative degree or equivalent experience and senior-IC depth building or validating models in a high-stakes domain such as credit fraud or financial crime.
• Command of effective-challenge methodology: reproduction conceptual-soundness review benchmarking stress testing and outcomes analysis with an eye for how a model holds up after launch and where its assumptions break.
• Deep applied ML and statistics across model families from regression and tree ensembles to deep learning with sound judgment about evaluation calibration and generalization.
• Experimentation and statistical rigor: holdout and experiment design reasoning about uncertainty and evaluating a model beyond aggregate accuracy.
• Solid software and data engineering: production-quality Python SQL on large datasets and reproducible tested code.
• Fluency with modern AI: building with LLMs and agentic tools and the judgment to know when their output can be trusted.
• Familiarity with model risk management frameworks and fair-lending standards with the specifics learnable on the job.
• The communication to explain and defend your conclusions to model owners and senior stakeholders and the independence to operate under ambiguity.

Technologies We Use and Teach

• Python (NumPy Pandas scikit-learn LightGBM XGBoost PyTorch)
• AI dev tools: Claude Code Cursor Copilot; agent skills and frameworks for building LLM-powered tooling
• MLflow / Databricks; Prefect on GCP Vertex AI
• Snowflake and cloud object storage
• GitHub and CI (ruff pytest)
• Jira and Linear
• GCP and AWS

Block takes a market-based approach to pay and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate's starting pay will be determined based on job-related skills experience qualifications work location and market conditions. These ranges may be modified in the future.
To find a location's zone designation please refer to this resource . If a location of interest is not listed please speak with a recruiter for additional information.
Zone A:
$189000 - $283600 USD
Zone B:
$179600 - $269400 USD
Zone C:
$170100 - $255100 USD
Zone D:
$160700 - $241100 USD
Application Guidelines
Candidates may submit up to 9 active applications within a 60-day period. Reapplications to the same role are accepted 90 days after a previous application has been reviewed.
Use of AI in Our Hiring Process
We may use automated AI tools to evaluate job applications for efficiency and consistency. These tools comply with local regulations including bias audits and we handle all personal data in accordance with state and local privacy laws.
Contact us here with hiring practice or data usage questions.
Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work medical insurance flexible time off retirement savings plans and modern family planning are just some of our offering. Check out our other benefits at Block.
Block Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend send and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together we're helping build a financial system that is open to everyone.