Enterprise ML Solutions Architect & MLOps Leader

U.S. Bank; San Francisco (CA); On-site; USD 139,000 - 164,000; Full time

Benefits offered by this job

Healthcare (medical, dental, vision)

Life insurance

Disability insurance

Parental leave

401(k)

Paid vacation

Paid holidays

Adoption assistance

Sick leave

Job summary

U.S. Bank is seeking an Emerging Technology Solutions Architect – Machine Learning to evaluate, design, and guide adoption of ML technologies across the enterprise.

The role focuses on identifying ML capabilities, assessing enterprise fit, and defining scalable solutions for analytics, predictive modeling, and AI-driven outcomes while aligning to enterprise standards. The candidate will partner with data science, data engineering, platform engineering, and risk/security teams to define

Qualifications

• Bachelor’s degree or equivalent work experience.
• 8+ years in software/ML/data engineering or solution architecture.

Responsibilities

• Evaluate emerging ML technologies for enterprise adoption.
• Define scalable architectures for end-to-end ML lifecycle.
• Lead production ML solutions with strong technical depth.
• Provide guidance on MLOps, model governance, and scaling.
• Collaborate with data science, data engineering, and risk teams to enable implementation.
• Translate complex concepts for technical and non-technical stakeholders.

Skills

ML & software architecture

MLOps

Cloud ML platforms

ML frameworks

Model serving & deployment

Explainability & governance

Communication & leadership

Generative AI awareness

Education

Bachelor’s degree or equivalent

Tools

Azure Machine Learning

AWS SageMaker

Databricks

Snowflake ML

MLflow

Kubeflow

Job description

U.S. Bank is seeking an Emerging Technology Solutions Architect – Machine Learning to evaluate, design, and guide adoption of ML technologies across the enterprise.

The role focuses on identifying ML capabilities, assessing enterprise fit, and defining scalable solutions for analytics, predictive modeling, and AI-driven outcomes while aligning to enterprise standards. The candidate will partner with data science, data engineering, platform engineering, and risk/security teams to define