Applied AI/ML Lead: Document Understanding & MLOps

JPMorgan Chase Bank, N.A.; Tampa (FL); On-site; USD 150,000 - 230,000; Full time

Job summary

JPMorgan Chase & Co. in Tampa, FL seeks a senior ML Engineer to lead design and deployment of AI/ML solutions for document processing, including image classification, text categorization, and data extraction from scanned documents.

You will build scalable pipelines on AWS SageMaker and EKS, advance OCR/text understanding, guide a team of ML engineers, and partner with software teams to deliver production-grade, high-throughput inference.

Qualifications

• Degree in Computer Science, Mathematics, OR Data Science or related field.
• 7+ years in applied ML/AI roles with 2+ years leading teams or large initiatives.
• Strong Python and enterprise-language proficiency with ML libraries.
• Expertise in CV/NLP models and multimodal document understanding.

Responsibilities

• Lead design, development, and deployment of AI/ML for document processing.
• Develop and fine-tune models for document understanding and data extraction.
• Integrate OCR tech and generative AI into production pipelines on AWS.
• Build scalable ML pipelines on SageMaker; deploy services on AWS EKS.
• Establish MLOps, model versioning, retraining, and monitoring dashboards.
• Lead ML engineers and applied scientists to meet business KPIs.

Skills

Python

Java

Groovy

PyTorch

TensorFlow

Hugging Face Transformers

OpenCV

Pillow

Oracle databases

AWS SageMaker

Amazon Bedrock

MLOps

MLflow

SageMaker Pipelines

Kubernetes

Docker

Education

Bachelor's degree or MS or PhD in quantitative discipline

Tools

Docker

Kubernetes

Oracle databases

AWS SageMaker

Amazon Bedrock

Job description

JPMorgan Chase & Co. in Tampa, FL seeks a senior ML Engineer to lead design and deployment of AI/ML solutions for document processing, including image classification, text categorization, and data extraction from scanned documents.

You will build scalable pipelines on AWS SageMaker and EKS, advance OCR/text understanding, guide a team of ML engineers, and partner with software teams to deliver production-grade, high-throughput inference.