• Collaborate with data scientists to develop, train, and evaluate machine learning models. • Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring. • Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment. • Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency. • Develop and implement monitoring systems to track model performance and identify issues. • Conduct A/B testing and experimentation to optimize model performance. • Work closely with data scientists, engineers, and product teams to deliver ML solutions. • Stay updated with the latest trends and advancements

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. The Role 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. You Will 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 You Have 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 Technologies We Use and Teach Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.) 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 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. Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

• Design, develop, and deploy AI models such as Generative AI solution (e.g., Large Language Models (LLMs)), Agentic AI, or AI powered tools working with large datasets and a variety of data, structured and unstructured, to create analytic insights and streamline business processes • Evaluate analytic solutions and business processes to recommend optimization through emerging technologies and AI/ML techniques • Remain current on AI technologies, advancements, solutions, and optimization methods to recommend and apply continuous advancement of AI solutions • Support multiple programs and evaluate overarching solutions, frameworks, and techniques to maximize the value of emerging technology • Lead project teams to design, develop and deliver complex solutions that achieve strong business value timely and efficiently • Extract qualitative and quantitative relationships, patterns, and trends from large amounts of data using various tools such as Python, R, SQL, etc. • Perform data analysis, statistical analysis, and machine learning modeling to conduct complex studies, develop sound inferences, and summarize results using a variety of descriptive statistics • Work with a variety of customers, users, and stakeholders to understand business objectives and design technical solutions to address the business needs • Collaborate within project teams including other data scientists and non-technical subject matter experts to achieve high quality and impactful solutions within tight timelines

• Provide leadership and strategic mentorship on the management of large-scale HPC systems including the deployment of compute, networking, and storage • Develop and improve our ecosystem around GPU-accelerated computing including developing scalable automation solutions • Build and nurture customer and cross-team relationships to consistently support the clusters and address changing user needs • Support our researchers to run their workloads including performance analysis and optimizations • Conduct root cause analysis and suggest corrective action • Proactively find and fix issues before they occur • Build innovative tooling to accelerate researchers' velocity, troubleshooting, and software performance at scale