Senior MLOps Engineer
Core
Design, develop, and support scalable MLOps platforms and pipelines for model development, deployment, monitoring, and retraining.
Role type
Senior hands-on IC MLOps Engineer
Builds
Scalable MLOps platforms, CI/CD workflows, data pipelines, feature engineering processes, and model-serving infrastructure
Domain
Machine Learning Operations (MLOps) / Cloud Infrastructure
Deliverable
production ML models
Required skills
MLOps, CI/CD workflows, Python, software engineering, REST APIs, microservices, containerization (Docker), ML lifecycle management, model monitoring, automated retraining
Preferred skills
Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage, Composer/Airflow)
Technologies
Airflow, BigQuery, Cloud Composer, Docker, Git, GitHub, Python, REST, microservices
Responsibilities
Design and develop scalable MLOps platforms and pipelines; build and automate CI/CD workflows for ML models; develop and manage data pipelines and feature engineering processes; deploy and maintain ML models in cloud-based production settings; implement model monitoring, alerting, and automated retraining workflows; create APIs embedding ML capabilities into enterprise systems; partner with cross-functional teams to productionize ML models; diagnose and resolve production issues affecting ML workloads; apply software engineering best practices including testing and code reviews