Job Description
**Job Description**
As a Senior MLOps Engineer, you will be responsible for building and operating the tooling, infrastructure, and automation that enable machine learning models to be trained, evaluated, deployed, and monitored reliably across development, test, and production environments. You will lead the adoption of MLOps best practices across Engineering and Data Science teams and develop strategies and platforms that allow models to be continuously delivered, governed, and iterated on as part of a modern cloud-native AI/ML platform.
**Responsibilities**
Own the ML platform infrastructure (training, serving, feature store, model registry) with attention to cost, reliability, and security.
Lead initiatives to improve observability and monitoring for data pipelines and ML services, including data drift, model performance, and latency.
Provide on-call support for production ML services; drive incident management and disaster recovery for ...
As a Senior MLOps Engineer, you will be responsible for building and operating the tooling, infrastructure, and automation that enable machine learning models to be trained, evaluated, deployed, and monitored reliably across development, test, and production environments. You will lead the adoption of MLOps best practices across Engineering and Data Science teams and develop strategies and platforms that allow models to be continuously delivered, governed, and iterated on as part of a modern cloud-native AI/ML platform.
**Responsibilities**
Own the ML platform infrastructure (training, serving, feature store, model registry) with attention to cost, reliability, and security.
Lead initiatives to improve observability and monitoring for data pipelines and ML services, including data drift, model performance, and latency.
Provide on-call support for production ML services; drive incident management and disaster recovery for ...