Anmol Chhabra

Summary

Integrated SageMaker pipelines, streamlined code documentation, and optimized model features for scalability and accuracy. Devised a lightweight ETL pipeline that migrated 50,000+ data points from Airtable and Shopify to PostgreSQL, using paginated data transfer, task automation, and schedulers. Led the refresh of NG Instant Loan credit Machine Learning models (FTB and RB) using Python, AWS, SageMaker, and Snowflake, enhancing training samples, and model performance through data sampling, feature drift analysis, and stability tests.

Summary

Optimized Samsung's Reader View by analyzing parsing functions and node evaluation criteria across top 50 news articles. Enhanced the core functionality of 2G GSGB module, involving Network programming, with Unit tests in GTest. Built a Visualization tool using Python, Flask, and Graphviz to transform complex SQL queries into graphical representations.

Summary

Architected an optimized schema for concurrent operations on DynamoDB and S3, leveraging AWS Lambda and API Gateway, with testing using Pytest and Boto3, resulting in approximately 30% faster query performance. Created an analytics dashboard with interactive UI Design, charts, and events using Chart.js, Headless UI, and Redux. Implemented feature of Chat with Voice and automated JSON data processing with AWS Step Functions.

Summary

- Automated Key rotation workflows for GCP and Azure using APIs and CLI, integrated with Slack bot for on-demand triggers. - Implemented PromQL-based memory and storage monitoring in Ansible playbooks, with custom alerting thresholds and detailed logging, resulting in 35% faster issue resolution. - Developed a Slack bot using Bolt, AWS Lambda and SQS, with features like Acknowledge, Nudge, Escalate, and TagOnCall, integrated logging in CloudWatch and deployment on ECR, utilizing DevContainers, and Linux CLI tools for local development.