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AI Engineer with less than a year in AI/ML & Full-Stack Development
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Smriti Yadav is an aspiring AI Engineer with hands-on internship experience in R&D at DRDO and SRTD at ISRO. She has developed and optimized VR simulations, analyzed satellite imagery with OpenCV, and engineered full-stack applications using RAG architecture and MERN stack. Her expertise spans Python, AI/ML frameworks like TensorFlow and PyTorch, cloud platforms, and robust system design. She is actively involved in projects like Context-Aware Q&A with RAG Architecture and Wildlife Conservation using AI, demonstrating a strong foundation in AI/ML and software development.
Manipal University Jaipur
B.Tech · Information Technology
August 1, 2022 – June 30, 2026
Lucknow Public School
Class 12th, CBSE Board
June 1, 2020 – May 31, 2021
Lucknow Public School
Class 10th, CBSE Board
June 1, 2018 – May 31, 2019
Space Applications Centre (SAC), ISRO
SRTD Intern
July 1, 2025 – October 31, 2025
Ahmedabad, Gujarat, India
INMAS, DRDO, Ministry Of Defence
R&D Intern
June 1, 2024 – August 31, 2024
New Delhi, Delhi, India
Context-Aware Q&A with RAG Architecture
June 1, 2026 – Present
Architected a full-stack, anti-hallucination Q&A system using a Retrieval-Augmented Generation (RAG) pipeline, achieving 97% factual accuracy against provided documents. Built a high-performance backend with FastAPI and LangChain, integrating Pinecone vector search achieving 3ms query latency and Cohere reranking to optimize response quality. Deployed the React (Vite) frontend and Python backend via a complete CI/CD pipeline using Vercel and Render, ensuring automated testing and seamless updates.
View ProjectFull-Stack Pharmaceutical Website
June 1, 2026 – Present
Engineered a production-grade MERN platform with modular React components, API-driven rendering, and Cloudinary-hosted assets, enabling seamless multi-page navigation and resulting in a 35% improvement in page load performance and responsiveness across devices. Built a secure backend with Express, MongoDB Atlas, and authenticated SMTP via GoDaddy + Nodemailer, powering verified corporate communication and improving inquiry processing reliability by 100% compared to unverified email workflows.
View ProjectWildlife Conservation using AI
April 1, 2025 – Present
Training and fine-tuning CNN and Transformer models (PyTorch/TensorFlow) on the BIRDS 525 dataset to classify 500+ bird species with a target accuracy of 98%. Analyzing eBird geospatial data to map spatiotemporal migration patterns, providing key data visualizations for biodiversity conservation (in support of SDG Goal 15).
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an AI Engineer role through their diverse project portfolio, which includes both cutting-edge AI research (RAG, CNN/Transformer models) and practical applications (wildlife conservation, satellite imagery). Their experience with various technologies (Python, JavaScript, DevOps tools) and internships at government research organizations (ISRO, DRDO) indicates a broad interest in technology and a willingness to engage with challenging, impactful work. The personal projects also show initiative and a drive for continuous learning, which are valuable traits for dynamic tech environments.
Soft Skills & Operational Fit
The candidate's project descriptions highlight a results-oriented approach, focusing on metrics like accuracy, latency, and performance improvements. Their involvement in diverse projects suggests adaptability and a proactive learning attitude. The structured descriptions indicate good communication skills for technical concepts. However, without direct interaction or psychometric test results, a deeper assessment of stress handling, teamwork, and leadership potential is not possible.