Senior MLOps Engineer

Job Summary

A company is looking for a Senior MLOps Engineer to design, build, and scale systems for AI capabilities.

Key Responsibilities

• Design and maintain end-to-end ML pipelines for model training, evaluation, and deployment
• Build and optimize infrastructure for distributed training and model serving across GPU and cloud environments
• 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 working with Python, C, C++, and Bash
• Proven experience deploying and managing ML models in production
• Proficiency with Docker and Kubernetes for scalable ML system design
• Experience with cloud platforms (AWS, GCP, or Azure) and GPU orchestration