MLOps/DevOps/CloudOps

Position Overview:

• Minimum of 2 years of experience in DevOps and Cloud MLOps, proficient in Python for scripting and automation tasks
• Expertise in Jenkins, Git, Docker, and EKS with strong troubleshooting capabilities
• Experience with AWS services including SageMaker, Lambda, S3, ECS, and IAM for infrastructure setup
• Proficient in Infrastructure as Code (IaC) using CloudFormation (CFT) and Terraform
• Experience in building and operating MLOps pipelines, deploying models to SageMaker, Databricks, or Lambda

Primary Duties:

• Design, implement, and sustain CI/CD pipelines for machine learning and application deployments
• Develop and manage MLOps frameworks for model training, deployment, monitoring, and retraining
• Automate infrastructure provisioning through Infrastructure as Code (IaC) methodologies
• Deploy and oversee machine learning models in live production settings
• Monitor application and model performance to ensure consistent availability and reliability
• Manage containerized applications utilizing Docker and Kubernetes
• Work closely with Data Scientists, ML Engineers, and Development teams to optimize deployment processes
• Enforce security compliance and governance best practices across cloud environments
• Enhance cloud infrastructure for improved scalability, performance, and cost-effectiveness
• Diagnose production issues and conduct thorough root cause analyses

Supplementary Responsibilities:

• Utilize Python for Information Retrieval and Text Processing within DevOps CI/CD Monitoring
• Work with Docker, Git, MLflow for model serving, monitoring, debugging, version control, and CI/CD in Kubernetes environments
• Engage in Prompt Engineering and the use of AI Coding Assistants

Desired Skills:

Technology->AI-AI Engineering->MLOps, Technology->AI-Data science->PYTHON, Technology->Cloud Platform->Amazon Web Services DevOps