AIML DevOps Engineer

Cloud Hybrid Technologies, LLC; Scottsdale (AZ); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading cloud technology provider is seeking a hands-on AIML DevOps Engineer in Scottsdale, AZ. The ideal candidate will possess over 6 years of experience in DevOps / CloudOps / MLOps roles and have strong expertise in GCP and AWS ML services, along with containerization tools like Docker and Kubernetes. Responsibilities include designing ML pipelines, managing cloud infrastructure, and automating workflows. The company values diversity and is committed to equal opportunity employment.

Qualifications

• 6+ years of experience in DevOps / CloudOps / MLOps roles.
• Strong experience with GCP AI/ML services or AWS ML stack.
• Hands-on experience with containerization and orchestration tools.
• Proficiency in Infrastructure-as-Code tools.
• Expertise in CI/CD pipelines using various tools.
• Programming experience in Python, Bash, or Go.

Responsibilities

• Design, build, and maintain ML pipelines for AI/ML models.
• Manage and optimize cloud-based ML infrastructure.
• Develop and manage CI/CD pipelines for AI/ML applications.
• Implement observability and monitoring for model performance.
• Automate workflows for data ingestion and model deployment.
• Work with data scientists and ML engineers for scalable operations.
• Apply MLOps best practices for continuous improvement.

Skills

DevOps / CloudOps / MLOps

GCP AI/ML services

AWS ML stack

Containerization

Orchestration tools (Docker, Kubernetes)

Infrastructure-as-Code tools

CI/CD pipelines

Programming (Python, Bash, Go)

Job description

We are seeking ahands-on AIML DevOps Engineerto join our client’s growing AI/ML engineering team in Scottsdale, AZ. The ideal candidate will have strong experience incloud-based MLOps,automation, andDevOpspractices, with the ability to deploy, monitor, and scale AI/ML models efficiently in production environments.

Key Responsibilities

• Design, build, and maintainML pipelinesfor training, testing, and deploying AI/ML models.
• Manage and optimizecloud-based ML infrastructureusingGCP Vertex AI,AWS SageMaker, or similar services.
• Develop and manageCI/CD pipelinesfor AI/ML applications ensuring automated deployment and version control.
• Implementobservability and monitoringfor model performance, system health, and resource utilization.
• Automate end-to-end workflows fordata ingestion, model training, deployment, and monitoring.
• Work cross-functionally withdata scientists, ML engineers, and software developersto ensure scalable and secure operations.
• ApplyMLOps best practicesfor reproducibility, model governance, and continuous improvement.

Required Skills & Experience

• 6+ yearsof experience in DevOps / CloudOps / MLOpsroles.
• Strong experience withGCP AI/ML services(Vertex AI, BigQuery ML, AI Platform) orAWS ML stack(SageMaker, etc.).
• Hands-on experience withcontainerization and orchestrationtools –Docker, Kubernetes.
• Proficiency inInfrastructure-as-Codetools –Terraform, CloudFormation, or Deployment Manager.
• Expertise inCI/CD pipelinesusingJenkins, GitLab CI, GitHub Actions, or ArgoCD.
• Programming experience inPython, Bash, or Go, including ML frameworks such asTensorFlow, PyTorch, Scikit-learn.
• Strong understanding of DevOps automation, security, and scalabilityin AI/ML production systems.

Cloud Hybrid is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. Cloud Hybrid will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will Cloud Hybrid require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract