• Design, develop, and maintain advanced machine learning models and algorithms to solve complex business problems • Lead complex machine learning projects that solve business challenges and add value to the broader ZipRecruiter Business • Design the overall architecture and infrastructure for machine learning systems, ensuring scalability, efficiency, and robustness • Push the boundaries of what's possible in machine learning in your organization, finding new and innovative ways to use AI to drive business value • Provide leadership and set tone for Machine Learning Engineers at ZipRecruiter leveraging industry best practices and innovation • Stay up-to-date with the latest developments in machine learning and AI, and drive adoption of new techniques and technologies as appropriate

• Design, develop, and maintain machine learning models and algorithms to solve complex business problems • Identify patterns, trends, and anomalies in the data, and visualize insights using appropriate tools • Assess the performance of machine learning models using appropriate metrics, validation techniques, and testing datasets • Discover opportunities to optimize models by fine-tuning hyperparameters, feature selection, or employing regularization techniques to improve accuracy, performance, and scalability

• Lead a team of ML/Ops engineers in deploying and managing Machine Learning models. • Build and enhance capabilities to seamlessly integrate ML models into existing pipelines. • Collaborate with cross-functional teams to understand project requirements and ensure successful deployment. • Provide ongoing support to accommodate surges in requirements, focusing on scalability and efficiency. • Utilize Python for scripting and automation tasks. • Work with Cloud platforms, particularly Azure and GCP to optimize machine learning workflows.

• Define and execute on the long-term ML technical vision and strategy for the Trust organization, identifying key investments, architecting scalable solutions, and championing best practices that advance the state-of-the-art in production ML systems. • Serve as a technical leader and mentor to other ML and software engineers across the organization, providing guidance on complex architectural and modeling challenges, and raising the overall technical bar. • Drive and deliver large-scale, multi-quarter ML initiatives that span multiple teams, influencing roadmaps and ensuring alignment between platform and product • Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases. • Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact. • Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks. • Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases. • Examples include: Anomaly detection models, ML models for continuous risk evaluation, Multimodality and Agentic AI