HonorHealth
From HonorHealth's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
(Like you.) At HonorHealth, you’ll find something special.
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Great care starts with great people. (Like you.)
At HonorHealth, you’ll find something special. From humble beginnings in 1927 to one of Arizona’s largest nonprofit healthcare systems, our culture is built on warmth and neighborly kindness. Behind every smile is a highly skilled professional with deep expertise and an unwavering dedication to what matters most — caring for the health and well-being of people and communities across the greater Phoenix area.
The AI / ML DevOps Engineer designs, develops, deploys, and supports scalable machine learning solutions that enable advanced analytics and AI capabilities across HonorHealth. This role operationalizes models and pipelines, monitors performance, and partners with data, engineering, and stakeholders to deliver reliable solutions aligned to governance and data handling expectations. The role partners closely with data engineers, data scientists, AI model developers, platform teams, and business stakeholders to translate complex needs into production-ready deployments, monitor ongoing performance, and continuously improve AI/ML capabilities aligned to governance and operational standards.
Design and implementation of the environment that deploys scalable AI/ML solutions, including predictive models, large language model use cases, and agentic workflows that support clinical, operational, and business objectives.
Develops and maintains end-to-end machine learning and RAG pipelines supporting data ingestion, application feature engineering, training, evaluation, deployment, and lifecycle management.
Architects and supports production-grade DevOps practices, including CI/CD, model versioning, automated testing, monitoring, alerting, retraining, and rollback strategies.
Deploys and manages AI/ML applications in cloud environments, ensuring solutions are secure, reliable, performant, and operationally supportable.
Implements observability and performance evaluation practices to manage compute resource utilization, performance, and cost efficiency. Works with AI development team to a continuous improvement feedback loop.
Ensures AI/ML and agentic solutions comply with data governance, privacy, security, and responsible AI expectations, including HIPAA-aligned practices where applicable.
Creates and maintains technical documentation for deployments, workflows, operational procedures, assumptions, limitations, and support processes.
Troubleshoots complex pipeline, infrastructure, model, and integration issues; implements fixes and drives continuous improvement in operational stability and delivery efficiency.
Performs other duties as assigned.
Bachelors Computer Science, Data Science, Engineering, Artificial Intelligence, Machine Learning, Mathematics, Statistics, or a related quantitative field; or 4 years’ relevant experience. Required
3 years, of progressive experience in DevOps within a Cloud deployment in AI/ML Ops, data engineering, or related software engineering roles, including at least 1 year deploying and operating AI/ML production workloads. Required
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