Applied AI ML-Senior Associate
About The Position
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. In this role, you’ll apply strong technical judgment to choose the right approaches (including modern LLM-based methods where appropriate), evaluate performance with rigorous metrics, and ensure solutions are reliable, secure, and scalable in real-world environments. You’ll also contribute to improving data quality and feedback loops, monitoring models in production, and continuously iterating to reduce agent effort, shorten resolution times, and increase consistency and quality across operational workflows. As an Applied AI Engineer-Senior Associate within the Consumer & Community Banking Machine Learning team, you will work with agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Requirements
- Undergraduate and master’s degrees in Computer Science or similar , with training and work experience in LLM/NLP and search.
- Proven track record of building and scaling software and or machine learning platforms in high-growth or enterprise environments
- Experience in machine learning frameworks, ML Ops tools and practices.
- Strong proficiency in engineering programming languages (e.g., Python, Java) and infrastructure as code (e.g., Terraform, CloudFormation)
- Proficient in building AI Agents (e.g., LangChain, LangGraph, AutoGen), integration of tools (e.g., API) and RAG based solutions (e.g., open search)
- Hands-on experience with software development pipeline and orchestration tools (e.g., Jenkins, GitLab CI/CD)
Nice To Haves
- Optional, great to have - experience in developing large-scale machine learning solutions based on big data to solve real world problems (e.g. Classification, Regression, or Recommender Systems).
Responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
- Drive innovation in machine learning solutions, ensuring scalability, flexibility, and future-proof architecture
- Act as a thought leader and trusted advisor to executive leadership, providing strategic recommendations on machine learning initiatives and solutions
- Architect and oversee the development of next-generation machine learning models and systems leveraging cutting-edge technologies
- Ensure the platform supports complex use cases, including real-time predictions, big data processing, and advanced analytics
- Promote software and model quality, integrity, and security across the organization
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
