Senior Machine Learning Engineer (Modeling), Financial Crimes

Key Skills

AWS, BERT, Effective communication skills, Google Cloud Platform (GCP), Java Programming, Kotlin, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), NumPy, Pandas, Python Programming, Scikit-learn, Snowflake

Job Description

The Role

The CashApp Financial Crimes Machine Learning team is responsible for detecting, preventing, and reporting illegal activity across all markets in which Block operates. We work globally with partners in business, engineering, counsel and product to ensure we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform.

We leverage Machine Learning as a necessary part of our toolkit to fulfill our mission. We employ scalable solutions to monitor billions of dollars in transactions. We uncover and put an end to money laundering, terrorist financing, and other illegal activities before they impact our users. We are looking for senior MLEs who want to solve critical business problems using all tools necessary.

You Will

• 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 ensure that data can be leveraged effectively to build efficient solutions within our regulatory program
• Produce and maintain thorough documentation of our program 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 in the field, foster an environment of continuous learning, and apply new learnings when applicable
• Have a significant impact on influencing team culture and direction

You Have

• 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 of the following areas: 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
• Excellent written and oral communication skills, both technical and non-technical, and are comfortable working with a cross-functional, globally distributed team
• Natural curiosity and desire to grow and help shape all aspects of our team

Technologies We Use and Teach

• Python (NumPy, Pandas, Scikit learn, PyTorch, etc.) with occasional Kotlin and Java
• Snowflake, GCP, AWS, and orchestration tools such as Prefect and Airflow
• Transformer models (BERT, LLMs, etc.)

We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page.

While there is no specific deadline to apply for this role, U.S. roles are typically open for an average of 55 days before being filled by a successful candidate. Please refer to the date listed at the top of this job page for when this role was first posted.