Machine Learning Ops Engineer - Real Estate

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Requirements:

• 5+ years of experience in ML Ops, Data Engineering, or DevOps roles.
• Proficiency with cloud platforms such as GCP, AWS, or Azure, and ML Ops tools like Kubeflow, MLflow, or SageMaker.
• Expertise in containerization (Docker, Kubernetes) and CI/CD pipelines (GitLab CI, Jenkins, CircleCI).
• Hands-on experience with data pipeline orchestration tools like Airflow.
• Strong knowledge of data versioning, feature stores, and model lifecycle management.

Responsibilities:

• Build and manage automated, reproducible ML pipelines for data ingestion, training, validation, deployment, and monitoring.
• Develop scalable model-serving architectures, including containerized deployments, APIs, and real-time frameworks.
• Automate infrastructure workflows, establishing CI/CD pipelines for ML models with robust versioning and rollback mechanisms.
• Monitor model performance and data drift in production, ensuring accuracy and system health.
• Collaborate with cross-functional teams to promote best practices for ML reproducibility, scalability, and maintenance.