Senior MLOps Engineer

Job Summary

Focused on building and scaling technical infrastructure for AI/ML systems, the full-time Senior MLOps Engineer specializing in LLMOps will manage CI/CD workflows, automate model versioning, and enhance AI infrastructure in a remote environment.

Key responsibilities

• Build reusable CI/CD workflows for model training, evaluation, and deployment
• Automate model versioning, approval workflows, and compliance checks across environments
• Continuously evaluate and integrate state-of-the-art AI tools and drive AI reliability and governance

Required qualifications

• Strong background in scalable infrastructure, including containerization and orchestration (e.g., Docker, Kubernetes)
• Experience with infrastructure-as-code and deployment tools (e.g., Terraform, CI/CD pipelines)
• Knowledge of ML Ops best practices, including model versioning and automated evaluation
• Proficiency in deploying and maintaining LLM and agentic workflows in production
• Ability to write high-quality, maintainable software, primarily in Python