| Urgent and Direct client req AWS MLOps Architect at Remote, Remote, USA |
| Email: [email protected] |
| Hi professionals Good Afternoon How are you all Hope you all are doing well Below is the JD for the AWS MLOps Architect Please let me know if you have any suitable candidates please share their resumes Including contact details with their current location & which visa Urgent and Direct client req AWS MLOps Architect Prime vendor requirement Leading insurance institution, wants to hire a strong AWS MLOps Architect for 18 Months Contract opportunity based in New York, NY Title: AWS MLOps Architect Duration: 24 Months Location: Hybrid_ (New York, NY) Must Skills: AWS, Machine learning, Sage maker, Deployment and Migration. Must have at least 10 years of experience. Job Description: MLOPS - AWS Sagemaker Architect (MLOPs-Machine learning Operations) Required Experience: 10+ Years Duration Build and configure end-to-end MLOps pipeline on AWS cloud for model management, model deployment & service and model governance using AWS SageMaker. Use Amazon SageMaker Studio for development and tracking. Implement CI/CD pipelines using GITLAB to automate model deployment and updates, enabling rapid iterations and reducing time-to-market. Create Framework for deploying ML models to production environments using SageMaker endpoints and set up monitoring to track model performance and drift over time. Set up and run SageMaker Clarify bias analysis through Amazon Sagemaker Experiments to check the model for potential biases. Setup SageMaker Model Monitor to allow select data from a menu of options such as prediction output, and capture metadata such as timestamp, model name, and end point so that client can analyze model predictions based on the metadata. Create framework for Model governance. Use Model Dashboard from SageMaker Studio for implementing model governance solutions. Maintain logs for reproducibility, validation, conformity, and auditability. Use SageMaker model registry for model management and model tracking. Design & develop search service for discovering model(s) by its capabilities. Build basic UI for model(s) search based on the model metadata. Configure & integrate FEAST for adding features to the stores Add Cohort model explainability used in the deployment phase, specifically in the model validation step before deployment. Set up dashboards leveraging AWS Clarify and Experiments to provide scores detailing features. Implement static deployment strategies (using traffic routing patterns) to deploy ML model(s) - Blue/Green, A/B Candidate Skills And Qualifications AWS Sagemaker, Machine Learning Data science & Python language Very well Experienced in developing Data Integration and advanced analytics solutions. Machine Learning and Data Science: Strong understanding of machine learning algorithms, Data preprocessing techniques and feature engineering. AWS Sagemaker: In-depth knowledge of Amazon Sagemaker services: CI/CD/CT with AWS Sagemaker and GIT. Model management and model tracking using Sagemaker model registry. Thanks & Regards Akhil Reddy Administrative Assistant Keshav Consulting Solutions, LLC Phone: 9 1 9-439-7374 Email: [email protected] Address: 5470 McGinnis Village Place, Suite102, Alpharetta, GA, 30005, Website: www.keshavconsulting.com Keywords: continuous integration continuous deployment machine learning user interface Connecticut Georgia New York |
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| Tue Jan 16 18:56:00 UTC 2024 |