Real-Time Data Pipeline
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Summary
Designed a Kafka-based streaming pipeline to process 10K+ user activity logs/sec with fault-tolerant ETL, cutting data latency by 40% and enabling real-time insights for business operations.
About
Highly motivated Software Engineering student with a strong foundation in Machine Learning APIs, real-time data pipelines, and cloud microservices. Proven ability to deliver measurable impact, including reducing latency by 30%, enhancing forecasting accuracy, and automating workflows. Passionate about leveraging cutting-edge technologies to solve complex real-world problems and develop scalable solutions.
Work
Banthry AI
|Research Intern
India, Not Provided, India
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Summary
Designed and deployed ML models as production APIs using FastAPI and Docker, significantly reducing latency and enabling real-time analytics on AWS microservices.
Highlights
Engineered and deployed production-ready ML models as scalable APIs using FastAPI and Docker, successfully reducing inference latency by 30%.
Enabled real-time analytics capabilities on AWS microservices, providing critical, data-driven insights for enhanced operational decision-making.
Implemented robust deployment strategies for machine learning solutions, ensuring high availability and performance in a production environment.
Bharat Heavy Electricals Limited (BHEL)
|IT Intern
India, Not Provided, India
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Summary
Developed a predictive model using Random Forest and XGBoost to forecast job completion times, significantly cutting late delivery risk by 15%.
Highlights
Developed and implemented a predictive model utilizing Random Forest and XGBoost, achieving an RMSE of 0.08 for accurate job completion time forecasting.
Reduced late delivery risk by 15% through precise predictions, optimizing production planning and enhancing operational efficiency.
Processed over 50,000 records, applying advanced feature engineering and cross-validation techniques to improve model accuracy and reliability for production planning.
IIT Hyderabad
|SURE Research Intern
India, Not Provided, India
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Summary
Deployed secure SDN/NFV workflows using RSA, TLS/mTLS, ensuring 100% message integrity and 1-second failover, while automating network setup.
Highlights
Deployed and validated secure SDN/NFV workflows leveraging RSA, TLS/mTLS protocols, achieving 100% message integrity and a rapid 1-second failover rate.
Developed automation scripts for network setup, significantly reducing configuration time by 40% within a simulated ITSAR environment.
Contributed to research on robust and efficient network security protocols, enhancing system resilience and operational efficiency.
Education
IIIT Naya Raipur
Raipur, Chhattisgarh, India
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Bachelor's Degree
Computer Science and Engineering
Grade: GPA: 9.07/10.0
Not Provided
India, Not Provided, India
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Class 12th CBSE
General Studies
Grade: 95%
Skills
Programming
Python, C++, Go, SQL, JavaScript.
Frameworks
FastAPI, Flask, Django, Spring Boot, Node.js.
Cloud
AWS, Docker, Kubernetes, Terraform.
Data
Kafka, PostgreSQL, MySQL, ETL, Pandas, NumPy.
ML / AI
Random Forest, XGBoost, NLP Transformers, RAG, Feature Engineering.
Networking
Microservices, SDN/NFV, TLS/mTLS, Secure APIs.
Tools
Git, CI/CD, Agile, JIRA, Linux, Bash Scripting.
Projects
Legal Assistant Chatbot
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Summary
Developed a WhatsApp-integrated legal chatbot utilizing transformer NLP and RAG to automate FIR and rental document generation, reducing turnaround time from hours to minutes for 100+ real-world legal queries.