Required Skills & Qualifications:
• Python: Deep expertise in Python for scripting and automation.
• AWS: Strong experience with AWS services, particularly SageMaker, S3, and Lambda.
• Terraform: Proficiency in using Terraform for infrastructure-as-code on AWS.
• Docker: Extensive experience with Docker, including building, managing, and securing Docker images.
• Linux: Strong command-line skills in Linux, especially for Docker and system management.
• DevOps Experience: Azure DevOps (ADO): Significant experience in setting up and managing CI/CD pipelines in ADO.
• Git: Proficient in using Git for version control and collaboration.
• Additional DevOps Tools: Experience with Jenkins or other CI/CD tools is a plus.
• Experience & Education: 4 years of experience in combination of MLOps/DevOps/Data Engineering; Bachelor's degree in Computer Science, Engineering, or a related discipline.
• Experience with large language models and productionizing ML models in a cloud environment.
• Exposure to near real-time inference systems and batch processing in ML.
• Familiarity with data drift and model drift management.