Senior ML Solutions Architect — Enterprise AI & MLOps

U.S. Bank; Chicago (IL); Hybrid; USD 139,000 - 164,000; Full time

Benefits offered by this job

Healthcare

401(k) retirement plan

Paid vacation

Paid holidays

Parental leave

Adoption assistance

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 from Chicago.

You will partner with data science, data engineering, and risk teams to define scalable architectures for the ML lifecycle and enable secure production deployments. The role requires 8+ years in relevant technical roles, strong MLOps expertise, and hands‑on experience with cloud ML platforms.

Qualifications

• Bachelor’s degree or equivalent work experience.
• 8+ years of software engineering, machine learning engineering, data engineering, solution architecture, or related roles.
• Experience designing production ML systems in cloud environments.
• Hands‑on ML platforms experience and strong MLOps capabilities.

Responsibilities

• Evaluate emerging ML technologies and tooling for enterprise adoption.
• Assess ML tech including Azure ML, SageMaker, Databricks, Snowflake ML, and open‑source frameworks.
• Define scalable architectures for end‑to‑end ML lifecycle: data, features, training, deployment, monitoring.
• Recommend patterns based on performance, security, cost, scalability, and governance.
• Establish reusable MLOps patterns for model serving, retraining, monitoring, and observability.
• Design production ML solutions with depth to support engineering and data science teams.
• Evaluate vendor platforms for enterprise fit and long‑term viability.
• Partner with data scientists and engineers to operationalize models at scale.
• Provide technical leadership on ML architecture, MLOps, and production deployment strategies.
• Establish standards for governance, explainability, and responsible AI.
• Translate complex concepts into clear recommendations for stakeholders.
• Assess emerging ML tech and translate findings into enterprise recommendations.

Skills

Strong communication

Stakeholder alignment

Cross-functional leadership

MLOps

Azure ML

SageMaker

Databricks

Snowflake ML

MLflow

Kubeflow

PyTorch

TensorFlow

Scikit-learn

XGBoost

Education

Bachelor’s degree or equivalent work experience

Tools

Azure Machine Learning

AWS SageMaker

Databricks

Snowflake ML

MLflow

Kubeflow

PyTorch

TensorFlow

Scikit-learn

XGBoost

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 from Chicago.

You will partner with data science, data engineering, and risk teams to define scalable architectures for the ML lifecycle and enable secure production deployments. The role requires 8+ years in relevant technical roles, strong MLOps expertise, and hands‑on experience with cloud ML platforms.