AI/ML Enablement Lead Engineer - U.S. Bank

Key Responsibilities

• Architect and implement end‑to‑end AI/ML solutions, from data ingestion to model deployment, on cloud environments such as AWS.
• Lead a cross‑functional team of data scientists, engineers, and analysts to deliver production‑grade machine learning models.
• Establish MLOps best practices, including CI/CD pipelines, model monitoring, and automated testing.
• Collaborate with business stakeholders to translate financial use cases into scalable technical designs.
• Mentor junior engineers, conduct code reviews, and promote a culture of continuous learning and technical excellence.

Requirements

• 5+ years of experience building and deploying machine learning models in production, preferably in the financial services sector.
• Strong proficiency in Python and related ML libraries (e.g., scikit‑learn, TensorFlow, PyTorch).
• Hands‑on experience with AWS services such as SageMaker, Lambda, ECS/EKS, and data storage solutions.
• Solid background in data engineering concepts, including ETL pipelines, data warehousing, and big‑data tools.
• Demonstrated ability to design scalable cloud architectures and implement MLOps practices.