Senior MLOps Engineer

Job Summary

Leading the development of robust ML infrastructure, the full-time Senior MLOps Engineer will design, build, and scale systems for AI capabilities in a remote environment, ensuring efficient model deployment and performance monitoring.

Key responsibilities

• Design and maintain end-to-end ML pipelines for model training, evaluation, and deployment
• Build and optimize infrastructure for model serving across cloud providers
• Implement CI/CD best practices for ML systems, including automated testing and deployment workflows

Required qualifications

• 6-10+ years of experience in software or ML engineering, with at least 3+ years in MLOps or ML infrastructure
• Solid experience with Python, C, C++, and Bash
• Proficiency with Docker and Kubernetes for scalable ML system design
• Experience with cloud platforms (AWS, GCP, or Azure) and GPU orchestration
• Hands-on knowledge of CI/CD pipelines (GitHub Actions, Jenkins, or similar)