onsite
AI Platform Adoption & Enablement Lead - U.S. Bank
Software Engineer
Lead the adoption and enablement of AI platforms, driving model deployment, governance, and scalability across the organization using Python, Machine Learning, MLOps practices, and cloud services such as AWS and Kubernetes.
About the role
Key Responsibilities
- Define and execute the strategy for enterprise‑wide AI platform adoption, ensuring alignment with business objectives.
- Architect, build, and maintain scalable MLOps pipelines on AWS, leveraging Kubernetes for container orchestration.
- Collaborate with data scientists, engineers, and product teams to streamline model development, testing, and production deployment.
- Establish best practices, governance, and security standards for AI workloads, including model monitoring and version control.
- Provide technical mentorship, training, and enablement resources to accelerate AI competency across the organization.
Requirements
- 5+ years of experience designing and operating AI/ML platforms in a cloud environment (AWS preferred).
- Strong proficiency in Python and modern ML frameworks (TensorFlow, PyTorch, Scikit‑learn).
- Hands‑on experience with MLOps tools, CI/CD pipelines, and container orchestration using Kubernetes.
- Solid understanding of data engineering concepts, APIs, and data pipelines.
- Excellent communication skills and a proven track record of leading cross‑functional technical initiatives.
Skills
pythonmachine learningmlopsawskubernetes