> Markdown version of [/jobs/ext/119683-machine-learning-engineer-document-digitization-llms-vice-president](https://www.wearedevelopers.com/jobs/ext/119683-machine-learning-engineer-document-digitization-llms-vice-president). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - Document Digitization (LLMs)-Vice President - **Company:** JPMorgan Chase & Co. - **Location:** Jersey City, NJ, United States - **Salary:** $164,350.0 - $260,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Cloud Computing, Code Generation, Code Review, Computer Programming, Continuous Integration, Data Sharing, Distributed Systems, Elasticsearch, Python (Programming Language), Machine Learning, MongoDB, Neo4j, NoSQL, Systems Development Life Cycle, Tensorflow, Software Engineering, Pytorch, ReactJS, Large Language Models, Model Validation, Generative AI, Containerization, AngularJS, Scikit Learn, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Variational Autoencoders, Machine Learning Operations, Tools for Reporting, Front End Software Development, Terraform, Docker - **Published:** May 16, 2026 - **Apply:** https://dejobs.org/x/x/410EDC8990C34854AA05FE207C558CB0/job/ ## About the Role * 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 ## Description * 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. ## Related Videos - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) - [Event-Driven AI Agents: Orchestrating Long-Context Legal Processing at Scale](https://www.wearedevelopers.com/videos/100168-event-driven-ai-agents-orchestrating-long-context-legal-processing-at-scale) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Got AI ideas but no money? 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