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

Jersey City, NJ, United States

Pay
Pay not listedSimilar roles state $165K–$240K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Apply at JPMorgan Chase

What you’ll work on

Full posting
  • Design and deploy AI-powered document digitization solutions that extract information from diverse document types

  • Manage the AI/ML lifecycle from training and validation through deployment and monitoring

  • Build and maintain scalable document digitization pipelines using Python and cloud technologies

  • Reimagine legacy document processing systems using generative AI and LLMs

  • Mentor junior engineers on AI/ML, software engineering, and testing best practices

From the employer’s posting
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.
Build and maintain scalable document digitization pipelines using Python, AI frameworks, and cloud technologies.
Collaborate with cross-functional teams to reimagine legacy document processing systems using generative AI and LLMs.
Mentor junior engineers and promote best practices in AI/ML, software engineering, and testing.
Education & alternatives
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).

Tools in this posting

  • Java
  • Python
  • AWS
  • Docker
  • Elasticsearch
  • Kubernetes
  • MongoDB
  • Neo4j
  • NoSQL
  • SageMaker
  • Terraform
  • PyTorch
  • scikit-learn
  • TensorFlow
  • React
Source — Tool mentions in context
- 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.
- 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).
- 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.
- 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 in design reviews, code reviews, and mentoring teams. - AWS Generative AI Developer – Professional certification or equivalent.
- 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.
- 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.

Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 28, 2026 · 1 day ago
Recorded sightings
6
Last seen by us
Oct 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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  • Check the listed location, eligibility and core experience before starting.
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Job description

View original posting ↗

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.
Source details

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Jersey City, NJ, United States

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