Applied AI ML - Senior Associate - Healthcare

About the role

As a Vice President and Applied AI/ML Lead at JPMorganChase within Payments Technology in the Commercial & Investment Bank, you will lead the delivery of document extraction and natural language processing capabilities that improve trust, safety, and operational effectiveness. You will own solutions end-to-end, from problem framing and data strategy to production deployment and measurement. You will remain hands-on while setting technical direction and partnering across product, engineering, data, risk, and compliance stakeholders.

Responsibilities

• Own end-to-end delivery of document extraction and natural language processing solutions, from opportunity sizing and requirements through production rollout and iteration.
• Design scalable model pipelines for document ingestion, text extraction, classification, and ranking, balancing accuracy, latency, throughput, and cost.
• Develop and improve natural language processing algorithms and model approaches to extract entities, relationships, and signals from unstructured text and documents.
• Define evaluation strategies and success metrics, including offline validation, error analysis, robustness testing, and controlled online measurement where appropriate.
• Establish model lifecycle practices including reproducibility, testing, monitoring, drift detection, and incident response to sustain reliable production performance.
• Partner with risk and compliance stakeholders to ensure appropriate documentation, controls, explainability expectations, and audit-ready processes.
• Drive technical decisions through design reviews, code and model reviews, and pragmatic standards that raise quality and delivery velocity.
• Communicate tradeoffs and recommendations to senior stakeholders, translating model behavior into decision-ready business impact.

Required qualifications, capabilities, and skills

• Formal training or certification on applied artificial intelligence and machine learning concepts and 3+ years applied experience
• 3+ years of experience building and delivering applied machine learning or natural language processing solutions with measurable outcomes in production.
• Strong programming skills in Python and experience using modern machine learning frameworks such as PyTorch or TensorFlow.
• Hands-on experience with document extraction and natural language processing techniques including text classification and information extraction.
• Experience designing data-driven solutions using SQL and distributed processing tools such as Spark or equivalent.
• Experience deploying and operating machine learning services or pipelines in a cloud environment such as Amazon Web Services (or equivalent).
• Demonstrated ability to translate ambiguous business problems into structured machine learning plans, including data strategy, evaluation, rollout, and operationalization.
• Strong communication and collaboration skills, including the ability to explain technical tradeoffs to technical and non-technical partners.

Preferred qualifications, capabilities, and skills

• Experience with optical character recognition and document understanding workflows for scanned or semi-structured documents.
• Experience with modern natural language processing architectures such as transformer-based models and techniques for optimization and efficient inference.
• Experience with machine learning operations practices and tooling, including model registries, continuous integration and delivery for machine learning, and observability.
• Experience with real-time or event-driven architectures supporting low-latency inference and feature generation.
• Experience applying document extraction or natural language processing in payments, financial services, or regulated environments.