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 ML  Engineer 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.

Job 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

Required qualifications, capabilities, and skills

• 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) 

   

   

Preferred qualifications, capabilities, and skills

• 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).