Senior MLOps Engineer

Job Summary

A company is looking for a Senior MLOps Engineer to develop and maintain infrastructure for efficient machine learning model lifecycle management.

Key Responsibilities

• Design and implement scalable, automated infrastructure using cloud services and container technologies
• Establish robust infrastructure to support complete ML deployment pipelines including CI/CD, versioning, testing, and monitoring
• Ensure ML models are production-ready by resolving performance, scalability, reliability, and security issues

Required Qualifications

• Several years of experience in software engineering, DevOps, or MLOps, focusing on ML infrastructure
• Expertise in container orchestration (e.g., Kubernetes, Helm)
• Proficiency in deploying ML-supportive open-source software (e.g., Metaflow, MLFlow)
• Solid knowledge of AWS and Linux-based systems
• Strong scripting abilities in Python and Bash