Description

MLOps Engineer with experience designing, deploying, automating, and monitoring machine learning solutions in production environments. Skilled in bridging the gap between Data Science, Machine Learning, and DevOps by building scalable MLOps pipelines, implementing CI/CD processes, managing model lifecycle operations, and ensuring reliable model performance. Proficient in Python, MLflow, Docker, Kubernetes, cloud platforms, and machine learning deployment frameworks. Experienced in developing secure, automated, and scalable infrastructure that enables efficient delivery of AI and machine learning solutions

Key Skills

Education

Bachelor's degree