Job Description :

Title: ML Ops

Location: Santa Clara, CA

Required Experience/Skills:

- ML Ops expert

- 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.

Role and Responsibilities:

- 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.

             

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