What you will do:

• Deploy, manage, and optimize Kubernetes clusters specifically tailored for AI/ML workloads, ensuring optimal resource allocation and scalability across different network configurations.
• Develop and maintain CI/CD pipelines tailored for continuous training and deployment of machine learning models, integrating tools like Kubeflow, MLflow, ArgoFlow or TensorFlow Extended (TFX) etc.
• Collaborate with data scientists to oversee the deployment of machine learning models and set up monitoring systems to track their performance and health in production.
• Design and implement data pipelines for large-scale data ingestion, processing, and analytics essential for machine learning models, utilizing distributed storage and processing technologies such as Hadoop, Spark, and Kafka.