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Senior Machine Learning Engineer, Financial Crimes at Block
BlockBay Area, CA, United States of America·5d ago
SeniorFull-timePythonJavaAWSGCPMachine LearningPyTorchAIML
Salary Range
$132,600 - $179,400 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Machine Learning Engineer to join the CashApp Financial Crimes team at Block. This role involves detecting, preventing, and reporting illegal activity across all markets in which Block operates. You will work globally with partners in business, engineering, counsel, and product to ensure a safe user experience while minimizing bad activity on our platform.
Key Responsibilities
- →Design, develop, and deploy machine learning models to detect and prevent financial crimes such as money laundering, human exploitation, and terrorist financing
- →Collaborate closely with stakeholders, business partners, and product engineering teams to leverage data effectively within our regulatory program
- →Produce and maintain thorough documentation that can withstand regulatory scrutiny
- →Proactively identify new opportunities and future needs of our ML teams
- →Lead by example by applying ML and engineering best practices
- →Stay current on ML developments and apply new learnings when applicable
Requirements
- ✓6+ years of machine learning experience with a focus on modeling and deployment
- ✓A degree (preferable graduate level) in Computer Science, Engineering, Statistics, Physics, Applied Math, or a related technical field
- ✓Expertise in at least one area: Natural Language Processing, Graph Neural Networks, Reinforcement Learning, or model explainability
- ✓Prior experience working with product, engineering, and business to prioritize, scope, design, and deploy ML tooling and infrastructure at scale
- ✓Ability to clearly convey both technical and non-technical concepts while collaborating with cross-functional, globally distributed teams
- ✓Natural curiosity and desire to grow and help shape all aspects of our team
