MLOps Engineer
Experience Required: 2+ years in MLOps/DevOps with at least 2 AI/ML projects delivered.
Responsibilities:
- Deploy, monitor, and maintain ML models in production.
- Implement CI/CD pipelines for AI/ML projects.
- Automate model retraining, scaling, and drift detection.
- Ensure model versioning, reproducibility, and audit compliance.
- Collaborate with Data Scientists and Engineers to streamline model deployment lifecycle.
Requirements:
- Experience with containerization (Docker, Kubernetes) and cloud ML services.
- Hands-on with MLflow, Kubeflow, SageMaker, or Azure ML.
- Proficiency in Python and scripting for automation.
- Understanding of monitoring tools (Prometheus, Grafana, ELK stack).
- Familiarity with data security, compliance, and governance.
Job Type: Full-time
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