AI - ML DevOps Engineer

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AI - ML DevOps Engineer in USA new

HonorHealth
Full time
Email

USA
11/08/2026
Report

Remote

Responsibilities

Design and implement environments for scalable predictive-model, large-language-model, and agentic AI/ML solutions.
Develop and maintain end-to-end machine learning and RAG pipelines covering data ingestion, feature engineering, training, evaluation, deployment, and lifecycle management.
Implement CI/CD, model versioning, automated testing, monitoring, alerting, retraining, and rollback practices.
Deploy and manage AI/ML applications in cloud environments with attention to security, reliability, performance, and operational supportability.
Implement observability and performance evaluation to manage compute utilization, performance, and cost efficiency.
Collaborate with data engineers, data scientists, AI model developers, platform teams, and business stakeholders to deliver production-ready deployments.
Ensure AI/ML and agentic solutions meet data governance, privacy, security, responsible AI, and applicable HIPAA-aligned expectations.
Document deployments, workflows, operational procedures, assumptions, limitations, and support processes.
Troubleshoot pipeline, infrastructure, model, and integration issues and improve operational stability and delivery efficiency.

Requirements

Bachelor's degree in Computer Science, Data Science, Engineering, Artificial Intelligence, Machine Learning, Mathematics, Statistics, or a related quantitative field, or four years of relevant experience.
Three years of progressive DevOps experience in cloud deployment, AI/ML operations, data engineering, or related software engineering, including at least one year deploying and operating production AI/ML workloads.
Hands-on experience with cloud-native AI/ML services and infrastructure, preferably Google Cloud Platform, including training, inference, orchestration, and scalable compute services.
Proficiency in MLOps, DevOps, and software engineering practices including Git-based workflows, containerization, Infrastructure as Code, and automated testing.
Experience establishing connections through API calls and MCP servers.
Strong SQL and data engineering skills, including large-scale data processing, backend engineering, and enterprise data-platform integration.
Experience with API development and systems integration for embedding AI/ML capabilities into enterprise applications and workflows.
Strong analytical, problem-solving, communication, collaboration, documentation, and technical explanation skills.

Benefits

Remote work within Arizona, with occasional on-site work as needed.
Monday-Friday day shift.
Healthcare-system environment supporting clinical, operational, and business AI/ML applications.

HonorHealth

HonorHealth is a nonprofit healthcare system serving the greater Phoenix area, operating nine acute-care hospitals and a network of primary, specialty, urgent, and outpatient care sites. Formed in 2013 and headquartered in Scottsdale, Arizona, it also runs clinical research and medical education ...

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