You enjoy shaping the future of product innovation as a core leader, driving value for customers, guiding successful launches, and exceeding expectations. Join our dynamic team and make a meaningful impact by delivering high-quality products that resonate with clients.

As an AI Platform Product Manager for Model Serving capabilities within the CDAO, you will have the unique opportunity to drive the evolution of our ML platform's serving layer. Focused on enabling streamlined, scalable, and secure model serving in both batch and real-time environments, you will work to enhance our platform’s capabilities targeted towards Data Scientists and ML Engineers.

 

Job Responsibilities

Define and execute a strategic vision specifically for model serving, incorporating detailed milestones, deliverables, resource allocation, and timelines to drive platform enhancements. Develop and refine platform features to simplify the deployment and serving of machine learning models, ensuring robust support for both batch and real-time serving via Kubernetes-based architectures. Work with stakeholders across the various businesses (Investment Bank, Consumer Bank, etc.) and functional groups (Legal, Technology, Controls) to collect business requirements, create PRDs, and ship high quality products that solve business needs  Drive the development of products for streamlining the passage of models through the Model Development Lifecycle, reducing the time to market for model deployment while enforcing strict governance and operational controls throughout the model lifecycle. Innovation & Reliability: Drive continuous innovation and ensure the reliability, scalability, and security of the serving infrastructure, directly influencing best practices in containerized model deployments using Kubernetes.

 

Required Qualifications, Capabilities, and Skills

6+ years of experience in product management with a proven ability to lead and develop high-performing teams in a technology-driven environment. Demonstrated success in delivering enterprise-scale products, particularly in the realm of ML platform solutions. In-depth technical knowledge with a focus on ML lifecycle management, including model deployment and monitoring, with hands-on experience in implementing or managing Kubernetes-based systems for both batch and real-time model serving. Exceptional leadership and collaboration skills, with the ability to influence cross-functional technology teams and business stakeholders effectively. A strong agile mindset, adept at rapid prototyping, iteration, and incorporating early user feedback. Proven track record in defining product domain strategy and roadmap, with the capacity to balance short-term deliverables with long-term technological vision in complex, matrixed organizations. Expertise in Cloud computing architectures.

 

Preferred Qualifications, Capabilities, and Skills

Prior experience working in a highly matrixed, complex organization with a focus on establishing and scaling ML or data science platforms.