Machine Learning Operations Engineer
Core
Build and maintain cloud infrastructure, CI/CD pipelines, and MLOps frameworks to deploy and monitor machine learning models as production APIs.
Role type
Senior Machine Learning Operations Engineer (MLOps)
Builds
End-to-end ML inference pipelines, REST/gRPC APIs, and containerized ML backend services on Google Cloud Platform
Domain
Cloud Infrastructure & Machine Learning Operations
Deliverable
production ML models
Required skills
Python, Kubernetes, Google Cloud Platform (GCP), CI/CD pipelines, SQL/NoSQL databases, MLOps frameworks, containerization, cloud infrastructure design, performance optimization, vulnerability testing
Preferred skills
Experience with AWS or Azure, advanced cloud architecture design
Technologies
Python, Kubernetes, GCP, SQL, NoSQL, MLOps frameworks, REST API, gRPC
Responsibilities
Build and maintain cloud infrastructure including Kubernetes and virtual machines; Develop REST API and gRPC applications for model deployment; Integrate database systems with the software platform; Setup tools to monitor model drift and production performance; Develop and maintain CI/CD pipelines; Containerize ML applications and deploy on Kubernetes; Design and optimize cloud infrastructure for performance and cost; Provide testing frameworks for cloud services; Document processes and conduct code reviews; Establish AI platform features for the product roadmap.
Seniority
Senior, hands-on IC
