MLOPS

Job description

Required Qualifications: Proven experience working with Windows and Linux operating systems in production environments. Hands-on experience managing on-premises servers and Kubernetes clusters and Docker containers. Strong proficiency in Python programming, with a solid background in developing Python-based solutions and applications. Deep understanding of machine learning workflows, including practical knowledge of ML model training processes, frameworks, and evaluation. Proven experience in ML deployment development, including building out end-to-end model serving pipelines and managing the model lifecycle. Familiarity with monitoring and debugging tools, e.g., DataDog. Ability to troubleshoot complex issues in distributed systems. Experience with CI/CD pipelines for ML applications. Familiarity with AWS cloud platforms. Background in Site Reliability Engineering or DevOps practices. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills.