Proudct Manager, Machine Learning Lifecycle

Job Description

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm's data and AI journey across Asset & Wealth Management, Consumer & Community Banking, Corporate & Investment Bank, and Corporate function lines of business.

CDAO is at the forefront of artificial intelligence innovation, supporting a vast community of data and AI practitioners.

CDAO is responsible for developing and implementing solutions that support the firm's commercial goals by harnessing AI and ML technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

Within CDAO, the Machine Learning Product Management team focuses on building solutions that accelerate the model development life cycle, scale deployment lifecycle, and integrate with AI Apps.

The team owns the central platform and infrastructure services for the end-to-end ML workflow, including feature exploration, model prototyping, AI app visualization, and model deployment.

As a ML product manager within the Machine Learning Product Management team, you will be responsible for understanding client needs, designing solutions aligned with the team's strategic vision, and overseeing the strategy and delivery for the product.

You will work closely with cross-functional teams to deliver best-in-class products and capabilities for the firm.

As a Platform, we enable our users to more quickly and more efficiently build and deploy models, with enterprise scale, reliability, and governance.

Job responsibilities


* Define a strategic vision and roadmap for the platform that includes milestones, deliverables, resources, and timelines.

Translate user and business needs into strategy and actionable requirements.


* Drive the development of platform capabilities for streamlining the passage of models through the Model Development Lifecycle (MLOps), with the objective of reducing the time to value


* 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


* Collaborate across business areas including engineering, data science, client engagement, architecture, and UX teams to deliver impactful business outcomes


* Seamlessly integrate the DevOps experience with the MLOps experience and


* Drive resource efficiency of centrally shared AI infrastructure and services


* Drive the development of platform capabilities for streamlining data connectivity and consumption to AI/ML services at enterprise scale for model training and serving.


* Own maintains, and develops a product backlog that enables development to support the overall strategic roadmap and value proposition


* Build the framework and tracks the product's key success metrics


* Drive adoption and create awareness of firmwide solutions th...