MLOps Engineer

• Apply MLOps practices and manage the machine learning lifecycle
• Process data and automate ML workflows using Python
• Query and manage databases using SQL
• Use Google Cloud Platform (GCP) for MLOps and machine learning workflows
• Orchestrate workflows using Cloud Composer and Apache Airflow
• Schedule and manage data and ML pipelines
• Transform data and support analytics engineering with Dataform
• Automate and monitor pipelines
• Support CI/CD pipelines and ML model deployment
• Use containerization technologies such as Docker and Kubernetes

• Strong experience in MLOps practices and machine learning lifecycle management
• Proficiency in Python for data processing, automation, and ML workflows
• Strong knowledge of SQL and database querying
• Hands-on experience with Google Cloud Platform (GCP)
• Experience with Cloud Composer (Apache Airflow on GCP) for workflow orchestration
• Expertise in Apache Airflow for scheduling and managing data and ML pipelines
• Experience with Dataform for data transformation and analytics engineering
• Understanding of workflow orchestration, pipeline automation, and monitoring
• Experience with CI/CD pipelines and ML model deployment (preferred)
• Knowledge of containerization technologies such as Docker and Kubernetes (preferred)
• Fluent English

• Diversity and inclusion commitment
• Fair work environment
• ESG and CSR commitment