Python, AWS Sagemaker
- Design optimal Cloud Applications and Solution Development.
- Architecting, Planning and Implementation of cloud infrastructure (end-to-end Data Warehouse and Business Intelligence applications utilizing best practices from Data Architecture, Data Integration and Data Management solutions would be preferred).
- Prepare data and AI-ML Sandbox for Data Science.
- Perform hands-on research on new AWS services, as they are made available through AWS partnership.
- Conduct data wrangling of heterogeneous data using Azure Functions and feature engineering for AI-ML Models.
- Develop and optimize large enterprise databases and applications.
- Designing, Installing and Configuring relevant AWS partner applications (along with monitoring utilities).
- Build / Setup new utilities for efficiently managing AWS services for any implementation.
- Perform hands-on project implementation using various AWS services including Redshift and Sagemaker.
- Proficient in building scripts in Python and Linux.
- Expertise in executing AWS solution in both public and hybrid cloud setup.
- Hands-on experience on Amazon Web Services public cloud and their various services such as EC2, EBS, S3, SNS, SES, RDS, Sagemaker, Redshift, SFTP, AWS Directory Services, Kinesis, etc.
- Hands-on experience with building APIs for models, forecasting models AI-ML algorithms (supervised, unsupervised) and solid understanding of statistics.
- Excellent communication skills (must be able to interface with both technical and business leaders in the organization).
- AWS Certified Machine Learning Specialty - Certification is mandatory
Duration: 6 Months
Location: GGN / Pune / Chennai