Design, deploy, and maintain end-to-end ML risk solutions at scale to detect and prevent fraud, merchant risk, and credit loss. Partner with cross-functional teams, lead technical decisions, build ML tooling, monitor models in production, and investigate emerging abuse patterns to improve detection and decisioning.
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
We're hiring Senior and Staff Machine Learning Engineers to join Block's Risk Machine Learning organization, where teams apply ML at massive scale to detect, prevent, and reduce fraud and abuse across Cash App and Square.
This opening supports multiple senior-level roles, with team placement determined through a collaborative matching process based on your experience, interests, and current business needs. Today, we're growing teams focused fraud & abuse prevention, merchant risk, credit underwriting (consumer & commercial lending), buy-now-pay-later decisioning, AI-powered customer support & conversational AI, agentic automation for investigations, and model risk governance. We'd love to hear from you whether your background is in adversarial ML, NLP/LLMs, credit modeling, or model validation.
Across teams, your work will directly protect our ecosystem, reduce financial loss, and enable safe, seamless financial experiences for millions of customers, sellers, and families.
You Will
You Have
Technologies We Use and Teach
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.
The Role
We're hiring Senior and Staff Machine Learning Engineers to join Block's Risk Machine Learning organization, where teams apply ML at massive scale to detect, prevent, and reduce fraud and abuse across Cash App and Square.
This opening supports multiple senior-level roles, with team placement determined through a collaborative matching process based on your experience, interests, and current business needs. Today, we're growing teams focused fraud & abuse prevention, merchant risk, credit underwriting (consumer & commercial lending), buy-now-pay-later decisioning, AI-powered customer support & conversational AI, agentic automation for investigations, and model risk governance. We'd love to hear from you whether your background is in adversarial ML, NLP/LLMs, credit modeling, or model validation.
Across teams, your work will directly protect our ecosystem, reduce financial loss, and enable safe, seamless financial experiences for millions of customers, sellers, and families.
You Will
- Partner with product, engineering, data science, policy, and operations to design and productionize ML-driven risk solutions at scale
- Own end-to-end machine learning systems - from problem definition and modeling to deployment, monitoring, and iteration
- Lead technical decision-making within your workstreams and influence ML strategy and planning
- Build tooling and processes that improve the speed, reliability, and impact of the ML development lifecycle
- Apply state-of-the-art modeling techniques and third-party data sources to improve detection and decision-making
- Investigate emerging fraud, abuse, and risk patterns to proactively inform product safeguards and policy
- Collaborate closely with ML platform and engineering teams to ensure models operate reliably in real time and at scale
You Have
- 8+ years of industry experience in machine learning, applied AI, or related fields
- Bachelor's degree in a quantitative field (Computer Science, Engineering, Statistics, Physics, Applied Math); Master's or PhD preferred
- Proven experience independently designing, deploying, and maintaining ML solutions in production
- Strong familiarity with techniques such as tree-based models, deep learning, transfer learning, or reinforcement learning
- Experience influencing technical direction and collaborating with cross-functional partners at scale
- Strong communication skills, sound judgment, and an ownership mindset
- Curiosity and alignment with Block's mission of economic empowerment
Technologies We Use and Teach
- Python (NumPy, Pandas, scikit-learn, XGBoost, PyTorch, TensorFlow/Keras)
- PySpark, MLflow, workflow orchestration tools (Airflow, Prefect)
- GCP (Vertex AI), AWS
- Snowflake, MySQL, Tableau, Mode
- Containerization, CI/CD, and production ML best practices
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.
Cash App San Francisco, California, USA Office



The original Cash App office, home to more teams than any other. Right in the heart of the Mission District. Mezzanine library, floor to ceiling terrariums, and Karl the Frog.
Similar Jobs at Cash App
Blockchain • Fintech • Mobile • Payments • Software • Financial Services
As a Senior Growth Marketing Analyst, you'll analyze and report on growth marketing channels, identify performance trends, collaborate on marketing strategy, automate reporting, and enhance measurement methodologies.
Top Skills:
AppsflyerAutomation ToolsChatgptLookerModeSnowflakeSQLTableau
Blockchain • Fintech • Mobile • Payments • Software • Financial Services
As an Engagement Marketing Manager, you'll lead customer activation and habituation strategies, run experiments, collaborate cross-functionally, and drive growth using data analysis and AI tools.
Top Skills:
Ai ToolsBrazeIterableModeSalesforce Marketing CloudSQLTableau
Blockchain • Fintech • Mobile • Payments • Software • Financial Services
Manage the Bank Partnerships Marketing Collateral Review program, support partner engagement, improve workflows, and utilize AI for efficiency.
Top Skills:
AIAutomationDocumentation ToolsLlm-Assisted ReviewOrchestration SoftwareTicketing SystemsWorkflow Tools
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine




