Applied AI/ML Lead — Healthcare Document Intelligence

JPMorganChase; Tampa (FL); On-site; USD 160,000 - 240,000; Full time

Benefits offered by this job

Comprehensive health care coverage

On-site health and wellness centers

Retirement savings plan

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching

Job summary

JPMorganChase is seeking an Applied AI/ML Lead to drive end-to-end AI/ML programs for the Healthcare Provider team. You will architect, train and deploy models for document understanding, OCR and multi-modal data extraction from scanned TIFs, while integrating with enterprise microservices on AWS.

You will guide model development, experiment tracking and MLOps, collaborating with software teams to ensure low-latency inference in production.

Qualifications

• Bachelor's degree or MS/PhD in quantitative discipline.
• 7+ years of experience in applied ML/AI roles with leadership experience.

Responsibilities

• Lead end-to-end design, development and production deployment of AI/ML solutions for document processing.
• Enhance models for document understanding, text categorization, NER, and semantic analysis, combining text, layout and image features.
• Integrate OCR tech and generative AI into the pipeline; leverage Amazon Bedrock for foundation models and intelligent document understanding.
• Build scalable ML training and inference pipelines using AWS SageMaker; deploy microservices on AWS EKS.
• Establish MLOps practices, model versioning, retraining triggers, A/B testing, drift detection and monitoring.
• Design scalable data pipelines and infrastructure for large volumes of scanned documents.

Skills

Python

PyTorch

TensorFlow

Hugging Face

OpenCV

Pillow

Java

Groovy

OCR

AWS SageMaker

Amazon Bedrock

Kubernetes

Docker

GPGPU Inference

Education

Bachelor's degree

MS/PhD in quantitative discipline

Tools

Oracle

JVM ecosystems

AWS EKS

Job description

JPMorganChase is seeking an Applied AI/ML Lead to drive end-to-end AI/ML programs for the Healthcare Provider team. You will architect, train and deploy models for document understanding, OCR and multi-modal data extraction from scanned TIFs, while integrating with enterprise microservices on AWS.

You will guide model development, experiment tracking and MLOps, collaborating with software teams to ensure low-latency inference in production.