Machine Learning Engineer – Document Digitization (LLMs)-Vice President

Testing Site - JPMC; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

Testing Site - JPMC is seeking an experienced Machine Learning Engineer - Document Digitization (LLMs) to design, develop, and deploy secure AI-powered document processing solutions in a VP-level capacity. The role focuses on extracting insights from diverse documents and automating workflows with generative AI, LLMs, and cloud platforms.

You will mentor engineers, manage the full ML lifecycle, and collaborate across teams to drive governance, security, and measurable business impact in a

Qualifications

• Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or related field.
• Strong proficiency in Python programming; 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.
• Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, PyTorch Lightning).
• Knowledge of generative AI models (GANs, VAEs, transformers, diffusion models) and LLMs.
• Experience with AWS cloud platforms (SageMaker, Bedrock), containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform).
• Familiarity with NoSQL databases (Mongo Atlas, ElasticSearch, OpenSearch, Neo4J).
• Experience with agentic coding approaches, autonomous code agents, and last sprinting code generation.
• Strong understanding of SDLC, CI/CD, resiliency, and security practices.
• Demonstrated ability to accelerate development using AI technologies.
• Experience deploying and maintaining AI/ML solutions in large-scale, production environments.

Responsibilities

• Lead the design, development, and integration of 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 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 Terraform and AWS services (SageMaker, Bedrock).
• Ensure scalability, reliability, security, and governance of AI/ML solutions in line with best practices.
• 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 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.

Skills

Python

Java

Front-end basics

ML/AI development

ML frameworks

Generative AI

LLMs

AWS SageMaker

AWS Bedrock

Docker/Kubernetes

Terraform

NoSQL databases

CI/CD

Security practices

SDLC

Autonomous coding

Problem solving

Communication

Education

Bachelor's/Master's in CS/DS/ML

Tools

Docker

Kubernetes

SageMaker

Bedrock

Terraform

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)-Vice President in our organization, 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

• Lead the design, development, and integration of 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 in Computer Science, Data Science, Machine Learning, or related field, with relevant industry experience.
• Strong proficiency in Python programming; 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.
• Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, PyTorch Lightning).
• Knowledge of generative AI models (GANs, VAEs, transformers, diffusion models) and LLMs.
• Experience with AWS cloud platforms (SageMaker, Bedrock), containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform).
• Familiarity with NoSQL databases (Mongo Atlas, ElasticSearch, OpenSearch, Neo4J).
• Experience with agentic coding approaches, autonomous code agents, and last sprinting code generation.
• Strong understanding of SDLC, CI/CD, resiliency, and security practices.
• Demonstrated ability to accelerate development using AI technologies.
• Experience deploying and maintaining AI/ML solutions in large-scale, production environments. and strong problem-solving, communication, and collaboration skills.

Preferred qualifications, capabilities, and skills

• Experience in financial services, especially investment banking or credit risk operations
• Expertise in agentic AI frameworks, prompt optimization, and fine-tuning SLMs
• Familiarity with distributed computing, data sharing, and DDP training
• Experience in design/code reviews and mentoring teams
• AWS Generative AI Developer Professional certification or equivalent