Enterprise ML Solutions Architect & MLOps Leader

U.S. Bank; Gresham (OR); On-site; USD 139,000 - 164,000; Full time

Job summary

U.S. Bank is seeking an Emerging Technology Solutions Architect – Machine Learning to drive evaluation, design, and adoption of machine learning technologies across the enterprise.

You will partner with data engineering, platform engineering, data science, and risk/security teams to define scalable patterns and enable secure implementation of AI-driven business outcomes. The role emphasizes hands-on solution design, architecture leadership, and governance of ML solutions at scale, with emphasis

Qualifications

• Bachelor’s degree or equivalent work experience.
• Eight (8) or more years of experience in software engineering, machine learning engineering, data engineering, solution architecture, or related technical roles.

Responsibilities

• Evaluate emerging machine learning technologies, platforms, frameworks, and tooling ecosystems for enterprise adoption.
• Assess ML technologies and services including Azure Machine Learning, AWS SageMaker, Databricks, Snowflake ML, and open-source ML frameworks.
• Define scalable architectures supporting the end-to-end machine learning lifecycle, including data ingestion, feature engineering, model training, deployment, monitoring, and governance.
• Recommend architecture patterns based on performance, scalability, security, explainability, and operational risk requirements.
• Establish reusable solution patterns for MLOps, model serving, feature stores, automated retraining, model monitoring, and observability.
• Design and recommend production-ready machine learning solutions with sufficient technical depth to support engineering and data science teams through implementation.
• Evaluate vendor platforms and ecosystem offerings for enterprise fit, long-term viability, and business value.
• Partner with data scientists and engineering teams to operationalize machine learning models at scale.
• Provide technical leadership on machine learning architecture, MLOps, model lifecycle management, and production deployment strategies.
• Establish standards and best practices for model governance, observability, explainability, and responsible AI.
• Translate complex technical concepts into clear recommendations for technical and non-technical stakeholders.
• Assess emerging machine learning technologies and translate exploratory findings into enterprise-ready recommendations.

Skills

ML fundamentals

Cloud ML systems

MLOps

ML platforms

ML frameworks

Model lifecycle

Data pipelines

Education

Bachelor's degree or equivalent

Tools

Azure ML

AWS SageMaker

Databricks

Snowflake ML

MLflow

Kubeflow

Job description

U.S. Bank is seeking an Emerging Technology Solutions Architect – Machine Learning to drive evaluation, design, and adoption of machine learning technologies across the enterprise.

You will partner with data engineering, platform engineering, data science, and risk/security teams to define scalable patterns and enable secure implementation of AI-driven business outcomes. The role emphasizes hands-on solution design, architecture leadership, and governance of ML solutions at scale, with emphasis