Staff Machine Learning Engineer (Modeling), Financial Crimes (Cash App)

Company Description
It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 47 million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.
Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.
Check out our locations, benefits, and more at cash.app/careers.
Job Description
The Financial Crimes Technology team at Cash App detects and reports illegal and suspicious activity on Cash App. We work globally with partners in Product, Counsel and Engineering to ensure that we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform.
We are leveraging Generative AI (specifically Large Language Models) and Machine Learning as an integral part of our toolkit to fulfill our mission. As Cash App scales, we monitor hundreds of billions of dollars in transactions across traditional payment and blockchain networks. Our machine learning systems monitor and surface suspicious activity (money laundering, illegal activity and terms of service violations) for agent review. Our systems also proactively block payments in real time where appropriate. Now, we are also leveraging generative AI technologies to improve agent workflow and case review tools; by adding features that accelerate agent productivity and enable them to make faster, more informed and accurate decisions.
This is a new and significant opportunity to rethink and optimize Financial Crimes Operations at CashApp scale. This is an IC role, but the Staff level has significant leadership responsibilities that include owning, and driving strategic roadmaps & priorities to completion by collaborating with relevant cross functional stakeholders.

• Experiment and deploy AI copilot and self-driving solutions at scale to improve agent productivity and/or eliminate manual decision loops altogether
• Own the end to end pipeline including API calls to disparate data sources, advanced prompt tuning and/or model fine tuning, metrics and evaluation, and integrating Gen AI output into production case generation systems
• Leverage LLMs to accelerate label generation to alleviate cold start problems for traditional ML classification problems
• Build classification models to detect illegal use of the app across the peer-to-peer, banking, card, equities and bitcoin products
• Leverage diverse data sets that include payment transactions, connected users and asset graphs, unstructured text data and user profile information to build ML and Generative AI models.
• Work with the embedded Machine Learning Engineers on the team and ML platform services to deploy models to the production environment and monitor ongoing performance
• Use Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, data platform and cloud services (both GCP & AWS) to get the job done

Qualifications

• 5+ years of Machine Learning modeling experience. Full stack ML experience is strongly preferred
• A Masters or advanced degree in computer science, data science, operations research, applied math, stats, physics, or a related technical field
• Experience with Large language models, and a background in traditional NLP techniques is a strong plus for this role
• End to end experience of building and deploying ML/AI to production systems (batch and real time) that are performant at scale
• Experience of independently owning, influencing and driving programs with multiple cross functional stakeholders that have significant business impact
• Have a curious, growth-oriented mindset and the ability to think in first principles to identify creative solutions that demonstrate value

Qualifications

• 5+ years of Machine Learning modeling experience. Full stack ML experience is strongly preferred
• A Masters or advanced degree in computer science, data science, operations research, applied math, stats, physics, or a related technical field
• Experience with Large language models, and a background in traditional NLP techniques is a strong plus for this role
• End to end experience of building and deploying ML/AI to production systems (batch and real time) that are performant at scale
• Experience of independently owning, influencing and driving programs with multiple cross functional stakeholders that have significant business impact
• Have a curious, growth-oriented mindset and the ability to think in first principles to identify creative solutions that demonstrate value