Profile Summary
Highly motivated Python Developer with 3+ years of experience specializing in backend development, RESTful API creation, and cloud-native solutions on AWS. Proven ability to design, build, and deploy scalable, efficient, and reliable systems using Python, FastAPI, Flask, Docker, and Kubernetes. Experienced in leveraging various AWS services, managing databases (SQL & NoSQL), implementing authentication, and optimizing system performance. Eager to contribute Python expertise to challenging projects and drive user-centric solutions.
Work Experience
- P2P SYSTEM PVT. LTD. | Python Developer
- Faridabad, India | FEBRUARY 2022 – PRESENT
Project: Automated Report Generation & Email Notification System
Developed a web-based document processing system to automate report generation and email notifications.
- Developed RESTful APIs using Python with AWS Lambda & API Gateway.
- Engineered asynchronous processing using SQS & Lambda triggered by EventBridge.
- Integrated ElastiCache (Redis) for API response time reduction.
- Implemented secure authentication and RBAC using Amazon Cognito (JWT).
- Containerized Python services using Docker deployed to AWS ECS (Fargate).
- Utilized DynamoDB for data storage and Kendra for document indexing.
- Managed file storage on S3 and configured SES for email alerts.
- Orchestrated workflows using Step Functions and EventBridge.
- Impact: 50% reduction in manual reporting effort, faster document processing.
Project: Multilingual AI-Powered Note-Taking Utility
Built a scalable, AI-powered, multilingual note-taking platform for construction workers.
- Built secure RESTful APIs using Python with FastAPI (async support).
- Integrated Whisper (Speech-to-Text) and Gemini Flash (Translation) models.
- Implemented Google Text-to-Speech for audio note generation.
- Developed JWT-based authentication and RBAC.
- Created language-agnostic indexing using Elasticsearch.
- Used PostgreSQL for structured data and S3 for media files.
- Managed asynchronous AI tasks using Celery with Redis.
- Containerized services with Docker, deployed on Kubernetes for scalability.
- Impact: Enabled seamless multilingual communication, cut documentation time by 50%, scaled to 100K+ notes/month.
Project: Predictive Maintenance for Equipment Failure
Developed an ML solution to optimize equipment maintenance schedules.
- Performed data exploration & feature engineering using Python (Pandas, NumPy).
- Handled imbalanced data using SMOTE.
- Built and evaluated ML models (Random Forest, XGBoost) using Scikit-learn/XGBoost.
- Used PR AUC for model evaluation.
- Outcome: Demonstrated potential for 18% reduction in maintenance expenses.
Education
- 2021 – 2025 (Expected)
- BS in Data Science and Applications
- Indian Institute of Technology (IIT), Madras
- CGPA: 7.93 / 10
- 2015 – 2019
- Bachelor of Engineering (Hons) in Mechanical Engineering
- Oriental College of Technology, Bhopal (RGPV)
- Percentage: 75.1%
- 2014
- Class XII (CBSE)
- Kendriya Vidyalaya, MP
- Percentage: 74.8%
- 2012
- Class X (CBSE)
- Kendriya Vidyalaya, MP
- CGPA: 9.2 / 10
Awards and Achievements
- Secured 'S' Grade (Highest) in Business Data Management (BDM) and Machine Learning Applications (MAD) projects at IIT Madras.
- Awarded Gold Medal in International Mathematics Olympiad.
- Selected for Zone level Science Exhibition participation.
Relevant Courses & Certificates
- 03/2022 – 08/2022
- Full Stack Data Science & AI
- Naresh IT (Hyderabad)
