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

Responsibilities

• Lead the design, development, and integration of AI powered document digitization solutions to extract information from diverse document types.
• Oversee the end-to-end AI/ML lifecycle: training, validation, deployment, monitoring, and production grade continuous improvement.
• Apply generative AI and large language models to automate and optimize document workflows.
• Build and maintain scalable digitization pipelines using Python, AI frameworks, and cloud technologies.
• Provision and manage cloud resources with infrastructure as code tools (Terraform) and AWS services such as SageMaker and Bedrock.
• Ensure scalability, reliability, security, and governance compliance of AI/ML solutions.
• Collaborate with cross functional teams to reimagine legacy document processing using generative AI and LLMs.
• Develop 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 reviews, and implement continuous improvement strategies for digitization accuracy.
• Contribute to communities of practice and explore new and emerging technologies.

Requirements

• Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or a related field with relevant industry experience.
• Strong proficiency in Python for building production grade AI services and data/document pipelines.
• Strong working proficiency in Java, including API and microservice development with Spring Boot; familiarity with front end technologies (React.js, AngularJS) is a plus.
• Hands-on experience delivering LLM powered or GenAI applications in production (document understanding, retrieval augmented generation, workflow automation) including evaluation, observability, guardrails, and continuous improvement.
• Experience with MLOps / LLMOps practices in production environments (CI/CD, automated testing, deployment strategies, monitoring, incident response).
• Working knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, PyTorch Lightning) focused on integrating models and services into scalable systems.
• Experience with AWS and cloud native delivery, including SageMaker and/or Bedrock, containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform).
• Familiarity with NoSQL / search / graph technologies (MongoDB Atlas, Elasticsearch/OpenSearch, Neo4j) and their use in document search and knowledge retrieval.
• Experience with agentic coding approaches, autonomous/assisted code agents, orchestration patterns, and tool-use/agent frameworks to accelerate digitization workflows.
• Strong understanding of SDLC, CI/CD, resiliency, and security practices; proven problem solving, communication, and collaboration skills.
• Demonstrated ability to accelerate development using AI technologies while maintaining engineering rigor (testing, code quality, governance).

Technologies

• Python
• Terraform
• AWS SageMaker
• AWS Bedrock
• Docker
• Kubernetes
• Amazon EKS
• Java
• Spring Boot
• React.js
• AngularJS
• TensorFlow
• PyTorch
• Scikit-learn
• PyTorch Lightning
• MongoDB Atlas
• Elasticsearch/OpenSearch
• Neo4j
• LLMs

Benefits

• Equity/stock-based compensation
• Competitive base salary
• Commission-based pay and/or discretionary incentive compensation
• Comprehensive health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching

About JPMorganChase

JPMorganChase is a long standing financial services institution serving consumers, small businesses, and large organizations worldwide under the J.P. Morgan and Chase brands. With a history spanning more than 200 years, the firm leads in investment banking, consumer and small business banking, commercial banking, payments processing, and asset management.

About the Team

Corporate Functions teams cover a broad range of areas from finance and risk to human resources and marketing. These professional groups play a key role in enabling business success for clients, customers, and employees across the organization.