DevSecOps Intern
Highlights
Supporting drone autonomy through automation and monitoring
Working on the migration of CI/CD pipelines from GitLab to GitHub Actions for FB2, the second version of FlytBase's flagship product.
Enhanced observability by configuring monitoring and alerting with Prometheus, Grafana, and Dynatrace.
Optimized workflows using reusable GitHub Actions, improving build and deployment efficiency across mi- croservices.
Engineering Intern (DevOps)
Highlights
AI-Enhanced DevOps: Proactive solutions for system optimization
Implemented MLOps using Dynatrace Davis AI for ECS clusters, automating actions via AWS Lambda when CPU saturation exceeded 95 percent, with notifications through GitLab CI/CD and MS Teams.
Monitored synthetic devices in Dynatrace to resolve blank device page errors caused by MSSQL/MySQL stored procedures.
Deployed AI-driven solutions using Docker, AWS (EKS/ECS), and enhanced CI/CD pipelines with GitLab CLI.
Research Intern
Highlights
Research and Development work on Deep Learning Algorithms BERT and GAN.
Applied development principles to produce clean, scalable, and testable code, resulting in a 30 percent improvement in algorithm efficiency and optimization.
Developed analytical skills, leading to a 15 percent improvement in the accuracy of data analysis methodologies.
Selected for the prestigious Amazon ML Summer School, gaining insights into advanced ML concepts and real-world applications.
Shortlisted among top 75 teams, advancing through multiple rounds of inter- views in the ZS Campus Beats Hackathon.
C++, Python, HTML, CSS, JavaScript.
DSA, OOPS, DBMS, Operating Systems.
ReactJs, Pandas, NumPy, Seaborn, Matplotlib, Sklearn.
MySql, MongoDB, MSSQL.
AWS, EC2/ECS, AWS Lambda, ELK, VS Code, Jupyter Notebook, GitHub, Kaggle.
Summary
Innovatively designed and implemented a dynamic Stock Listing App using Node.js and ReactJS, integrating real-time stock data from the Polygon API for up to 20 stocks simultaneously. Engineered user-centric features, including customizable watchlists and real-time notifications, resulting in better user engagement through Real Time Updates.
Summary
Developed a powerful generative language model in Python, leveraging Pytorch-Lib. Generated coherent and contextually relevant text, ideal for content generation, chatbots, and creative writing