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

JPMorganChase•Jersey City, NJ

About The Position

As a Machine Learning Engineer – Document Digitization (LLMs), Senior Associate, on the Global Technology team, you will design, develop, and deploy secure, scalable technology products that transform document processing and management. You will apply AI and machine learning to extract, analyze, and manage information, helping drive strategic business outcomes. The role involves collaborating with cross-functional teams, mentoring colleagues, and pursuing opportunities for improvement and innovation. You will develop AI-powered document digitization solutions and manage the end-to-end machine learning lifecycle, from training and validation through deployment, monitoring, and ongoing improvement in production. You will use generative AI and large language models to automate document workflows, build scalable pipelines with Python and cloud technologies, and provision infrastructure using Terraform and AWS services. You will also help ensure that solutions meet scalability, reliability, security, compliance, and governance standards.

Requirements

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 such as React.js or AngularJS.
Hands-on experience developing and deploying AI/ML models and using MLOps practices in production environments.
Experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, or PyTorch Lightning.
Knowledge of generative AI techniques, including GANs, VAEs, transformers, and diffusion models, and of LLMs.
Experience with AWS services such as SageMaker and Bedrock; containerization tools such as Docker, Kubernetes, and Amazon EKS; and Terraform.
Familiarity with NoSQL and search technologies such as MongoDB Atlas, Elasticsearch, OpenSearch, or Neo4j.
Experience using autonomous code agents and agentic development workflows for code generation and refactoring.
Understanding of the software development lifecycle, 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.

Nice To Haves

Experience in financial services, including investment banking or credit risk operations.
Experience with agentic AI frameworks, prompt optimization, and fine-tuning small language models.
Familiarity with distributed computing, data sharing, and distributed data parallel training.
Experience with design reviews, code reviews, and mentoring teams.
AWS Generative AI Developer – Professional certification or equivalent.

Responsibilities

Design, develop, and integrate AI-powered document digitization solutions that extract information and insights from diverse document types.
Manage the end-to-end AI/ML lifecycle, including model training, validation, deployment, monitoring, and continuous improvement in production.
Use generative AI and large language models 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, including SageMaker and Bedrock.
Ensure AI/ML solutions are scalable, reliable, secure, and compliant with 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, facilitate human-in-the-loop review, and implement strategies to improve digitization accuracy.
Contribute to communities of practice and explore emerging technologies.