Machine Learning Engineer; Modeling), Families Risk Bay Area, CA,

Remote Bay Area, CA, US

Posted Date: 10/29/25

Remote Bay Area, CA, US Req : R0004433 Posted Date: 10/29/25 Posted 2 days ago

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 50+ 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.

Machine Learning is an integral part of how we at Cash App design products, operate, and pursue our mission to serve the unbanked as well as disrupt traditional financial institutions. Our massive scale and deep trove of transaction data create an endless number of opportunities to use ML and AI methods to better understand our customers and offer new products and experiences that can improve their lives.

We are a highly creative group that prefers to solve problems from first principles; we move quickly, make incremental changes, and deploy to production every day.

As part of the Risk ML team, you will help shape the future of teen banking by developing models that enable safe and trustworthy financial experiences for teens and their parents. Your work will focus on building machine learning systems that detect and prevent risky or abusive activity, strengthen account integrity, and ensure a secure ecosystem for families on Cash App.

You ll experiment with state-of-the-art algorithms to identify emerging risk behaviors, detect potential abuse in real time, and help ensure that millions of customers can use Cash App safely and confidently.

• Build machine learning models to detect and act against risky or abusive activity across the Cash Families product
• Collaborate cross-functionally with engineering, product, and operations teams to design systems and features to protect and maintain trust with our customers
• Work closely with the ML Engineering teams who build the systems that allow our models to operate at scale and in real time
• Research emerging risks and behavioral patterns in financial activity to proactively shape safeguards and policy
• Contribute to the growth of our modelling capabilities through mentoring and supporting fellow modellers
• Exercise a high level of autonomy and responsibility, owning your solutions from design through to operation

• Bachelor s degree in a quantitative field such as Mathematics/Statistics/Physics or Machine Learning. Masters or PhD preferred
• 5+ years of experience in machine learning, artificial intelligence, or a related field
• Strong knowledge of machine learning algorithms and data analysis techniques
• Excellent problem-solving skills and attention to detail
• Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders

• MySQL, Snowflake, Tableau, Mode
• GCP/AWS

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…