About
Recently graduated Computer Science engineer (Honours: Full Stack Development) with hands-on experience building NLP systems, RAG pipelines, LLM-powered applications, and multimodal AI models. Skilled at designing and deploying end-to-end AI systems — from neural network architecture and model optimization through production integration.
Experience1
Software Engineering Intern
May 2025 — Jul 2025DeepMedIQ
Designed and integrated AI-driven data pipelines across 4+ REST API sources for a healthcare platform with over 1,000 users. Built and deployed NLP-assisted reporting features during 2 Agile sprint cycles, translating model outputs into actionable recommendations. Collaborated with engineering and product teams to define AI system requirements and maintained zero regression across 5+ production deployments.
Projects3
DeprAnalyser
Engineered 8 NLP/DL models for multimodal sentiment and emotion classification across 10,000+ text and audio samples, achieving 96.36% accuracy through iterative optimization. Developed a production-ready Next.js interface enabling natural language querying of model outputs.
- Python
- PyTorch
- TensorFlow
- HuggingFace
- ONNX
- Next.js
NextFlow
Architected a model-agnostic LLM orchestration platform enabling visual composition and execution of multi-step AI agent pipelines. Integrated Gemini API with Trigger.dev for async agent job orchestration, ensuring reliable workflow execution.
- Next.js 14
- TypeScript
- React Flow
- Gemini API
- PostgreSQL
- Trigger.dev
- Docker
- GCP
NeuroInsight
Designed and trained a 4-model deep neural network ensemble for complex pattern recognition across 3,000+ MRI scans, achieving over 96% classification accuracy. Published a peer-reviewed paper documenting the research.
- Python
- TensorFlow
- PyTorch
- OpenCV
- ResNet50V2
- U-Net
- CNN
Education1
B.Tech in Computer Science & Engineering
2022 — 2026VR Siddhartha Engineering College