MLOps Engineer - Atlanta, GA - Remote - W2

Role Overview

MLOps Engineer (W2) for AI/ML production support and operations. This role is responsible for keeping deployed machine learning systems running reliably, monitoring model health, and improving delivery/deployment workflows.

Responsibilities

• Provide L2/L3 production support for AI/ML applications, pipelines, and model deployments
• Monitor model performance, drift, and data quality in production
• Troubleshoot and resolve incidents, alerts, and failures across ML workflows
• Support CI/CD pipelines for model deployment and versioning
• Collaborate with Data Scientists, ML Engineers, and DevOps teams on fixes and enhancements
• Manage model retraining schedules, batch/real-time pipelines, and inference jobs
• Perform root cause analysis (RCA) and implement preventive actions
• Ensure SLA/SLO compliance and maintain operational dashboards/reporting
• Handle release support, patching, and environment maintenance
• Maintain documentation including runbooks, troubleshooting guides, and SOPs

Requirements

• 7+ years relevant experience in production/application support (AI/ML preferred)
• Hands-on troubleshooting experience with Python, SQL, and scripting
• Knowledge of the ML lifecycle (training, validation, deployment, monitoring)
• Cloud experience: Azure/AWS/GCP
• Familiarity with MLOps tools: MLflow, Kubeflow, SageMaker, Azure ML
• Docker and Kubernetes experience
• CI/CD exposure: Jenkins, GitHub Actions, Azure DevOps
• Monitoring tools: Grafana, Prometheus, ELK, Azure Monitor
• Strong debugging and incident management

Preferred Skills

• Healthcare/payer domain experience (claims, enrollment, analytics)
• Data engineering tools: Spark, Airflow, Databricks
• Model explainability and governance frameworks
• ITIL process knowledge (incident/problem/change)

Location & Employment

• Atlanta, GA (Remote)
• W2
• Contract duration: 12+ months