Join JPMorgan Chase and transform financial services with innovative AI. 

As a Applied AI ML Associate at JPMorgan Chase within the Consumer and Community Banking technology, you will be actively involved in development and deployment of scalable, secure, and high-quality machine learning solutions. You will collaborate with cross-functional teams, guide best practices, and architect next-generation AI platforms that power the future of banking. 

Job Responsibilities

• Design, develop, and maintain secure, high-quality production code.

• Review and debug code to ensure adherence to best practices and code quality.

• Champion software and model quality, integrity, and security across the organization.

• Influence product design, application functionality, and technical operations.

• Architect and oversee the development of advanced machine learning models and systems using cutting-edge technologies.

• Ensure platforms support complex use cases, including real-time predictions, big data processing, and advanced analytics.

• Drive innovation in machine learning, ensuring solutions are scalable, flexible, and future-proof.

• Advocate for firmwide frameworks, tools, and SDLC best practices within the engineering community.

Required Qualifications, Capabilities, and Skills

• Formal training or certification in software engineering concepts with 3+ years of applied experience.

• Expertise in developing, reviewing, and debugging secure, high-quality production code.

• Deep knowledge of machine learning, big data processing, and advanced analytics.

• Experience architecting scalable and flexible machine learning platforms.

• Demonstrated ability to drive innovation and influence technology adoption.

• Excellent communication skills, with the ability to advise and influence executive leadership.

• Technical proficiency in Python for software and model development, AWS Cloud for scalable solution deployment. Retrieval-Augmented Generation (RAG) and AI/Agents, Natural Language Understanding (NLU), Natural Language Processing (NLP), and Large Language Models (LLM)

• Experience with engineering and operational best practices ML Ops for operationalizing machine learning workflows, CI/CD pipelines for continuous integration and delivery, SDLC best practices for software development lifecycle management

 
Preferred Qualifications, Capabilities, and Skills

• Familiarity with firmwide frameworks, tools, and SDLC best practices.

• Track record of contributing to the engineering community and promoting best practices.

• Experience in RAG, AI/Agents, NLU/NLP, LLM