What are the responsibilities and job description for the Tech Lead Manager - AI/ML Solutions position at JPMorgan Chase?
Join us in reshaping the future!
as a Lead AI/ML Engineer (Tech Lead Manager) you will be responsible for ML feature development, ML model training, ML model deployment, Gen AI LLM approaches such as RAG and Agent. You will join the AI/ML Platform & Solutions Engineering team within our Consumer & Community Banking (CCB) division. In this role, you will assist our technical partners and data science teams by focusing on traditional AI/ML and Generative AI platform enablement to support line-of-business (LOB) machine learning use cases.
Job responsibilities
- Lead the design and development of our AI/ML platform, ensuring robustness, scalability, and high performance.
- Drive the adoption of best practices in software engineering, machine learning operations (MLOps), and data governance.
- Ensure compliance with data privacy and security regulations relevant to AI/ML solutions.
- Maintain consistent code check-ins every sprint to ensure continuous integration and development.
- Enable the Gen AI platform and implement the Gen AI Use cases ,LLM finetuning and multi agent orchestration
- Communicate technical concepts and solutions effectively across all levels of the organization.
Required qualifications, capabilities, and skills
- Master's degree in a STEM field and 10 years of experience in designing and managing large-scale AI & ML platforms and supporting systems.
- Extensive practical experience with AWS cloud services, including EKS, EMR, ECS, and DynamoDB.
- Experience in Databricks ML lifecycle development.
- Advanced knowledge in software engineering, AI/ML, machine learning operations (MLOps), and data governance.
- Demonstrated prior experience in leading complex projects, including system design, testing, and ensuring operational stability.
- Expertise in computer science, computer engineering, mathematics, or a related technical field.
Preferred qualifications, capabilities and skills
- Understanding of large language model (LLM) approaches, such as Retrieval-Augmented Generation (RAG) and agent-based models, is a plus.
- Real-time model serving experience with Seldon, Ray, or AWS SM is a plus.
