Lead Machine Learning Engineer

This senior role focuses on developing machine learning models to optimize return on ad spend (ROAS) for advertising campaigns. The scientist will build predictive models, conduct causal analysis, and collaborate with product teams to improve campaign performance and client outcomes.

Develops and deploys machine learning models on the AI platform, focusing on scalability and performance. Requires expertise in ML frameworks, model training, and deployment.

This role involves developing and maintaining the AI platform that powers Smartly's advertising solutions. The engineer will work on building scalable infrastructure for model training and inference, integrating ML models into production systems, and optimizing performance.

Acts as a Forward Deployed Engineer on the Cortex AI team, building and deploying enterprise-grade AI solutions and sophisticated AI agents for strategic customers. The role involves architecting AI pipelines from prototype to production, owning the full lifecycle of AI solution implementation, and serving as a technical advisor to customer data science teams. Requires strong Python and SQL skills to translate ambiguous business objectives into scalable solutions.

This Chief Product Officer role at ASAPP is responsible for leading the overall product vision, strategy, and execution for the company's AI-powered customer experience platform. The role involves overseeing the product organization, driving innovation, and ensuring alignment with business goals.

This Lead Machine Learning Engineer role owns and grows the evaluation platform for ASAPP's agentic AI systems, designing frameworks to measure quality, safety, and performance. The role involves working closely with research and modeling teams to build state-of-the-art NLP models and deploy them in production, ensuring that model changes are validated before reaching customers.

This role leads and builds the Agent Developer team within ASAPP's Delivery organization, designing frameworks, standards, and playbooks for developing and maintaining AI agents deployed for customers. It is a player-coach role requiring hands-on technical work, close partnership with Project Managers and Forward Deployed Engineers, and direct customer engagement to continuously improve agent development practices.