Senior DevOps/MLOps Engineer

Role overview Own infrastructure for computer vision software that runs in cloud environments and on servers deployed at customer sites. The role focuses on keeping these systems reliable and building the platform capabilities needed to deploy and manage a growing fleet of edge servers at scale.

Responsibilities - Maintain infrastructure supporting computer vision services in cloud and on-site environments. - Build systems for deploying and managing edge servers across multiple customer locations. - Support workloads running on managed Kubernetes and coordinate their operation across a fleet. - Help ensure platform and machine learning operations support software used in physical settings such as service centers, factories, and stores.

Requirements - The available description emphasizes Kubernetes and experience thinking about infrastructure across fleets of servers. - Further specific qualifications are not included in the available source material.

Benefits and work setup - Remote, full-time position. - Described as a high-trust role with ownership of platform and MLOps work.