Staff MLOps Engineer

Focused on building and scaling technical infrastructure for AI/ML systems, the full-time Staff MLOps Engineer 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 Partner with engineering and data science to integrate AI models into real-time applications 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