MLOps Architect

Over 12 years of experience, including more than 5 years in the MLOps Engineer role and 3 years as an MLOps Architect. Independent handling of at least three production deployments is required.

• Design and implement cloud solutions and build MLOps on cloud platforms (AWS, Azure, or GCP).
• Build CICDCL (Continuous Machine Learning) and CT (Continuous Training) pipeline orchestration using tools like MLflow, Kubeflow, Kubernetes, GitLab CI, GitHub Actions, CircleCI, Airflow, or similar.
• Communicate with teams of data scientists, data engineers, and application architects, and document processes.
• Assist in deploying machine learning models into production environments.
• Contribute to the monitoring and maintenance of model performance and infrastructure health.
• Participate in the development and maintenance of automated MLOps pipelines.
• Collaborate with cross-functional teams to integrate machine learning models into production systems.
• Maintain documentation of MLOps processes and procedures.
• Work closely with technology team members in the development and implementation of AI solutions, products, and platforms.
• Knowledgeable in agile practices.