ML Ops Engineer (Remote)

Posted 27 days agoViewed

View full description

💎 Seniority level: Middle, 4+ years

📍 Location: United States

🔍 Industry: SaaS

🏢 Company: Canibuild Au Pty Ltd

⏳ Experience: 4+ years

🪄 Skills: AWSDockerPythonGCPKubeflowKubernetesMachine LearningMLFlowAirflowAzureData engineeringCI/CDDevOps

Requirements:

4+ years in MLOps, AI infrastructure, or DevOps
Strong expertise in CI/CD tools for ML (e.g., MLflow, Kubeflow, Airflow)
Experience with cloud ML services (AWS SageMaker, Google Vertex AI, Azure ML)
Proficiency in container orchestration (Docker, Kubernetes)
Understanding of AI model monitoring, logging, and explainability frameworks

Responsibilities:

Implement CI/CD pipelines for model training, testing, and deployment.
Develop scalable ML infrastructure to ensure reliable AI model performance.
Automate model retraining, versioning, and monitoring using MLflow, Kubeflow, or Airflow.
Deploy ML models on cloud platforms (AWS, Azure, GCP) and manage Kubernetes/Docker environments.
Assist in optimizing data pipelines and integrating AI models with production systems.
Ensure AI deployments adhere to security, governance, and compliance standards.