Role: Machine Learning – Ops Expert
Location – Santa Clara, CA
JD:
· Design, develop, deploy, and maintain production-grade scalable data transformation, machine learning and deep learning code, pipelines; manage data and model versioning, training, tuning, serving, experiment and evaluation tracking dashboards.
· Manage ETL and machine learning model lifecycle: develop, deploy, monitor, maintain, and update data and models in production.
· Build and maintain tools and infrastructure for data processing for AI/ML development initiatives.
· Develop ETL pipelines, tools and processing jobs for data cleansing, labeling and analysis.
· Experience deploying machine learning models into production environment.
· Strong DevOps, Data Engineering and ML background with Cloud platforms
· Experience in containerization and orchestration (such as Docker, Kubernetes)
· Experience building/operating systems for data extraction, ingestion and processing of large data sets
· Experience with MLOps tools such as MLFlow and Kubeflow
· Experience in Python scripting
· Experience with CI/CD
· Experience with ML training/retraining, Model Registry, ML model performance measurement using ML Ops open source frameworks.