MLOps Engineer

MLOps Engineer | 7+ Years | Remote

JD

We are seeking an experienced MLOps Engineer with strong expertise in ML lifecycle management, Kubernetes, CI/CD, ML platform engineering, model deployment, monitoring, and cloud infrastructure. The ideal candidate will have hands-on experience operationalizing machine learning models, building scalable ML pipelines, and implementing production-grade MLOps solutions across AWS, Azure, or GCP environments.

Key Responsibilities

• Design and implement end-to-end MLOps workflows covering training, deployment, monitoring, retraining, and governance.
• Build scalable ML pipelines and automate model lifecycle processes.
• Deploy and manage ML models on Kubernetes-based platforms.
• Implement CI/CD pipelines for machine learning solutions.
• Develop experiment tracking, model versioning, and model registry frameworks.
• Monitor model performance, detect drift, and automate retraining workflows.
• Build dashboards, alerting mechanisms, and observability solutions.
• Collaborate with Data Scientists and Engineers to operationalize ML solutions.
• Implement Infrastructure as Code and cloud-native MLOps best practices.