Machine Learning Engineer - Document Digitization (LLMs)-Senior Associate

JPMorganChase; Jersey City (NJ); On-site; USD 140,000 - 190,000; Full time

Job summary

JP Morgan Chase is seeking a Machine Learning Engineer – Document Digitization (LLMs) to design, develop, and deploy secure AI-powered document processing solutions. The role focuses on extracting insights from diverse documents, training and deploying models, and driving improvements across production pipelines.

You will collaborate with cross-functional teams, mentor engineers, and ensure governance and security. A strong foundation in ML, cloud tech, and scalable architectures is required.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, ML, or related field.
• Proficiency in Python; familiarity with Java and front-end technologies (React.js, AngularJS).
• Hands-on experience with AI/ML model development, deployment, and MLOps in production.
• Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Knowledge of generative AI techniques and LLMs.
• Experience with AWS services (SageMaker, Bedrock), containers (Docker, Kubernetes), and Terraform.
• Familiarity with NoSQL/search (MongoDB Atlas, Elasticsearch, OpenSearch, Neo4j).
• Experience deploying AI/ML in production; strong problem-solving and collaboration.

Responsibilities

• Design, develop, and integrate AI-powered document digitization solutions, extracting information from diverse documents.
• Manage end-to-end AI/ML lifecycle: training, validation, deployment, monitoring, improvement.
• Use generative AI and LLMs to automate document workflows.
• Build scalable digitization pipelines using Python, AI frameworks, and cloud technologies.
• Provision and manage cloud resources with Terraform and AWS SageMaker/Bedrock.
• Ensure scalability, reliability, security, and governance of AI/ML solutions.
• Collaborate across teams to modernize legacy document processing with AI/LLMs.
• Develop dashboards to monitor digitization accuracy, efficiency, and impact.
• Mentor junior engineers and promote best practices in AI/ML and testing.
• Explore new technologies and contribute to communities of practice.

Skills

Python programming

MLOps

Distributed training

CI/CD

Mentorship

Education

Bachelor's or Master's in CS/Data Science/ML

Tools

Python

Java

React.js

AngularJS

Terraform

AWS SageMaker

AWS Bedrock

Docker

Kubernetes

MongoDB Atlas

Elasticsearch/OpenSearch

Job description

Are you passionate about leveraging advanced technology to solve complex business challenges? As an applied AI/ML, you will have the opportunity to shape the future of document management through cutting-edge AI and machine learning. Join a collaborative team where your expertise will drive impactful solutions and strategic outcomes. This role offers a platform to innovate, lead, and make a difference across the organization.

As a Machine Learning Engineer – Document Digitization (LLMs)- Senior Associate within the Global Technology team, you will design, develop, and deploy secure, scalable, and innovative technology products that transform how documents are processed and managed. You will use advanced AI and machine learning to extract, analyze, and manage information, driving strategic business outcomes. You will collaborate with cross-functional teams, mentor others, and continuously seek opportunities for improvement and innovation.

Job responsibilities

• Design, develop, and integrate AI-powered document digitization solutions, focusing on extracting information and insights from diverse document types.


• Manage the end-to-end AI/ML lifecycle: model training, validation, deployment, monitoring, and continuous improvement in production environments.


• Employ generative AI and large language models (LLMs) to automate and optimize document workflows.


• Build and maintain scalable document digitization pipelines using Python, AI frameworks, and cloud technologies.


• Provision and manage cloud resources using infrastructure as code tools (Terraform) and AWS services (SageMaker, Bedrock).


• Ensure scalability, reliability, security, and compliance of AI/ML solutions, adhering to best practices and governance standards.


• Collaborate with cross-functional teams to reimagine legacy document processing systems using generative AI and LLMs.


• Develop and maintain dashboards and reporting tools to monitor digitization accuracy, workflow efficiency, and business impact.


• Mentor junior engineers and promote best practices in AI/ML, software engineering, and testing.


• Conduct model validation, human-in-the-loop review, and implement continuous improvement strategies for digitization accuracy.


• Contribute to communities of practice and explore new and emerging technologies.

Required qualifications, capabilities, and skills

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field, with relevant industry experience.


• Proficiency in Python; familiarity with Java and front-end technologies (React.js, AngularJS).


• Hands-on experience with AI/ML model development, deployment, and MLOps practices in production environments.


• Experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn, PyTorch Lightning).


• Knowledge of generative AI techniques (GANs, VAEs, transformers, diffusion models) and LLMs.


• Experience with AWS services (SageMaker, Bedrock), containerization (Docker, Kubernetes, Amazon Elastic Kubernetes Service (EKS)), and infrastructure as code (Terraform).


• Familiarity with NoSQL and search technologies (MongoDB Atlas, Elasticsearch, OpenSearch, Neo4j).


• Experience using autonomous code agents and agentic development workflows for code generation and refactoring.


• Understanding of the software development lifecycle (SDLC), continuous integration/continuous delivery (CI/CD), resiliency, and security practices.


• Experience deploying and maintaining AI/ML solutions in large-scale production environments; effective problem-solving, communication, and collaboration skills.

Preferred qualifications, capabilities, and skills

• Experience in financial services, including investment banking or credit risk operations.


• Experience with agentic AI frameworks, prompt optimization, and fine-tuning small language models (SLMs).


• Familiarity with distributed computing, data sharing, and distributed data parallel (DDP) training.


• Experience in design reviews, code reviews, and mentoring teams.


• AWS Generative AI Developer – Professional certification or equivalent.