Senior AI/ML Engineer — Remote in AZ (MLOps & Cloud)

HonorHealth; Arizona; Hybrid; USD 140,000 - 190,000; Full time

Job summary

HonorHealth in Virtual Arizona seeks a Senior AI/ML Engineer to design, deploy, and support scalable ML solutions across the organization. You will operationalize models, build end-to-end pipelines, and partner with data, engineering, and stakeholders to deliver reliable AI capabilities aligned with governance expectations.

Lead MLOps practices, cloud deployments (GCP), and production-grade workflows, while maintaining strong data security and privacy compliance.

Qualifications

• Bachelor's degree or 4 years' experience in AI/ML engineering.
• 7+ years of progressive experience in AI/ML or related software roles.
• Strong SQL and data engineering skills.
• Experience with cloud-native AI/ML services and MLOps.
• Knowledge of privacy and security practices including HIPAA where applicable.

Responsibilities

• Leads design and implementation of scalable AI/ML solutions.
• Develops end-to-end ML pipelines from data ingestion to deployment.
• Architects production-grade MLOps with CI/CD and monitoring.
• Deploys AI/ML solutions in Google Cloud Platform.
• Ensures governance, privacy, and security in models and workflows.
• Creates technical docs for architectures and procedures.
• Collaborates with data, engineering, and stakeholders.
• Troubleshoots pipelines and improves reliability.

Skills

ML Engineering

Data Engineering

Cloud Computing

MLOps

CI/CD

API Development

SQL

Education

Bachelor's degree or 4 years' experience

Tools

Google Cloud Platform (GCP)

Terraform

Docker

Kubernetes

Git

Job description

HonorHealth in Virtual Arizona seeks a Senior AI/ML Engineer to design, deploy, and support scalable ML solutions across the organization. You will operationalize models, build end-to-end pipelines, and partner with data, engineering, and stakeholders to deliver reliable AI capabilities aligned with governance expectations.

Lead MLOps practices, cloud deployments (GCP), and production-grade workflows, while maintaining strong data security and privacy compliance.