The Risk AI team’s mission is to develop cutting-edge deep learning-based signals and learned representations for Risk ML models. Our focus is on exploring, developing, and implementing state-of-the-art (SOTA) alternatives to traditional feature-based machine learning methods. By leveraging the latest advancements in AI, we aim to enhance real-time evaluation pipelines used by the Risk ML team to detect and prevent fraudulent transactions and activities. Cash App holds people’s money, and maintaining customers’ trust is absolutely essential to our brand. Preventing scams and fraud is a major component of building that trust. The Risk AI team is at the forefront of this effort, utilizing SOTA approaches to drive innovation and protect our users from emerging threats.
What you’ll do:
Design, build and maintain Machine Learning systems that enable us to flag fraudulent activities in real-timeWork hand-in-hand with ML Modellers to identify and integrate new data sources, heuristics and modelsSolve challenging technical problems at scale, collaborating with colleagues located across the globeOwn your solutions from design through to operation: we all share the pager!Lead the conception, design, and implementation of large-scale experiments to validate novel ideas rapidly and comprehensivelyApply the latest theoretical advancements to enhance existing products, processes, and technologies, ensuring they remain at the forefront of the industryEngage in the creation of experiments, prototyping, and architectural design, contributing to a diverse range of computer science domains such as machine learning, data mining, natural language processing, and performance analysisTake the lead in designing systems, data structures, frameworks, and evaluation metrics for research solution developmentConduct experiments aligned with research inquiries, employing simulations and prototypes to assess the outcomes