Summary from listing
The ML Ops Engineer will design and operate scalable machine learning infrastructure and data pipelines, deploy and monitor production models, manage cloud and containerized environments, automate infrastructure and deployment processes, and collaborate with data science, IT, and OT teams. The role requires 5–7 years of experience and expertise in cloud platforms, Kubernetes, DevOps, monitoring, version control, infrastructure as code, scripting, data engineering, and distributed-systems troubleshooting.
