Job Description:Design, implement, and manage MLOps pipelines using Azure MLFlow, AWS SageMaker, Vertex.ai, Dataiku, and H2O.ai.Automate the deployment, monitoring, and scaling of machine learning models.Collaborate with data scientists and software engineers to integrate ML models into production environments.Ensure the reliability, scalability, and performance of ML solutions.Develop and maintain CI/CD pipelines for ML models.Monitor and troubleshoot ML models in production to ensure optimal performance.Stay updated with the latest advancements in MLOps and machine learning technologies.Requirements:Bachelor's or Master's degree in Computer Science, Engineering, or a related field.Proven experience as an MLOps Engineer or similar role.Strong proficiency in Azure MLFlow, AWS SageMaker, Vertex.ai, Dataiku, and H2O.ai.Experience with CI/CD tools and practices.Proficiency in Python and familiarity with ML frameworks (e.g., TensorFlow, PyTorch).Excellent problem-solving skills and attention to detail.Strong communication and teamwork abilities.Preferred Qualifications:Experience with other cloud platforms and MLOps tools.Knowledge of big data technologies (e.g., Hadoop, Spark).Certification in cloud platforms or MLOps technologies.
