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

JPMorgan Chase
Jersey City, USA
Full-time
Senior
Onsite
Discovered 1 weeks ago
awsbedrockdockerekselasticsearchjava

Full Job Posting

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.

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