ML Ops Engineer
Core
Build and operate platform capabilities to take machine-learning models from experimentation into reliable production services, focusing on automation, deployment, observability, and operational controls.
Role type
Senior IC ML Ops Engineer
Builds
Production ML services, CI/CD pipelines, model registries, and observability dashboards
Domain
Machine Learning Operations, Cloud Infrastructure, DevOps
Deliverable
production ML models
Required skills
Python, CI/CD pipeline design, model serving, containerization, infrastructure as code, observability, incident response, system design
Preferred skills
Model monitoring, drift detection, automated retraining, model registries, feature stores, PyTorch
Technologies
Python, PyTorch, Containers, Infrastructure as Code, Cloud providers
Responsibilities
Build repeatable workflows for model training, validation, promotion, deployment, and retraining; Deploy and operate batch and online inference services; Monitor service health, data drift, and model performance decay; Establish dashboards, alerting, and operational runbooks; Debug production issues across model, application, and infrastructure layers; Improve system robustness and cost efficiency through automation.
Seniority
Mid-Senior, hands-on IC