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.
, 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