Description
The MLOps Engineering role builds tools, automation, and end-to-end machine learning pipelines for developing, training, evaluating, and deploying ML models and intelligent agents. Responsibilities include monitoring, logging, tracing, distributed GPU-cluster systems, CI/CD, and optimizing workflows for reproducibility, scalability, and cost-efficiency. The role requires hands-on MLOps experience, a solid understanding of the ML lifecycle, end-to-end project ownership, and at least three years of Python experience.
