***** Direct Client Requirement*****
Title : Machine learning with Devops
Location : Santa clara, CA
Rate : DOE /If your experience and skills match call us immediately for submission
Duration : 12 Months
Interview Type : Skype Or Phone
Work Status : Successful applicants must be legally authorized to work in the U.S
Job Type : C2C,C2H,W2
Experience : 8 years
Prefer W2 : U S C/ G C /H1B Transfer/OPT/CPT/H4 EAD and other US work authorization are accepted
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.
*****Referral Bonus Available: Refer your friends or colleagues, get referral bonus******
Apply here or Please send to firstname.lastname@example.org
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Position Keywords: Python scripting,CI/CD,MLFlow and Kubeflow,ETL and machine learning
Pay Rate: DOE/If your experience and skills match call us immediately for submission
Job Duration: 12 Months
% Travel Required: None
Job Posted by: Consulting Services
Job ID: OOJ - 2963
Work Authorization: Successful applicants must be legally authorized to work in the U.S