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AI Research Engineer with 1+ years in Quantum Machine Learning & Fullstack Development
Highly motivated and results-driven AI Research Engineer with approximately 1 year of experience specializing in Quantum Machine Learning and full-stack development. Proven ability to design and implement hybrid Quantum-Classical ML models for financial forecasting, achieving significant accuracy improvements. Skilled in Python, JavaScript, and various AI/ML frameworks, with expertise in building robust, data-driven platforms and optimizing complex systems. Actively seeking roles that leverage strong analytical and technical skills in cutting-edge AI and software development.
Rajiv Gandhi Institute of Petroleum Technology
B.Tech. (IDD) · Computer Science and Engineering and AI
August 1, 2022 – June 30, 2027
BIEAP Board
Senior Secondary
N/A – May 31, 2021
SSC Board
Secondary
N/A – May 31, 2019
IIT(BHU), Varanasi
Research Intern
May 1, 2025 – August 1, 2025
Varanasi, Uttar Pradesh, India
Quantum Time-Series Forecasting using Hybrid QML
June 25, 2026 – Present
Developed hybrid Quantum-Classical pipeline using PennyLane for financial time-series forecasting. Applied 10-day sliding window preprocessing on OHLCV data for sequence modeling. Designed Quantum Autoencoder reducing feature dimension from 10 → 4 latent features. Implemented Variational Quantum Circuit (VQC) using parameterized quantum gates. Built complete pipeline including preprocessing, training, and evaluation using MSE, MAE, and R². Achieved improved performance over classical models with R² up to 0.96.
View ProjectFinVision AI – Full-Stack AI Finance Platform
June 25, 2026 – Present
Developed a full-stack finance platform using Next.js, Supabase, Prisma, Tailwind, ShadCN UI with authentication and dashboard UI. Integrated Gemini AI API for receipt scanning, transaction categorization, and financial insights. Implemented secure backend APIs and database schemas using Prisma ORM. Added email automation using Resend and role-based access via Clerk authentication. Optimized UI with responsive components, dynamic charts, and real-time updates.
View ProjectFinalist in Binary Clash 360 Hackathon
IIT Madras
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's academic projects showcase a strong interest in cutting-edge fields like Quantum Machine Learning and AI-driven finance, aligning well with an 'AI Research Engineer' role that values innovation and deep technical exploration. The diversity of projects (QML, full-stack AI platform) indicates a broad technical curiosity and adaptability. The research internship further solidifies a fit for a research-oriented environment. However, the candidate is still early in their career, and their long-term career aspirations and collaborative style would need further exploration to fully assess cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experience suggest an ability to work on complex technical challenges and collaborate on reproducible experiments. The hackathon finalist achievement indicates problem-solving skills under pressure. However, without direct assessment data for soft skills, a comprehensive evaluation of work attitude, stress handling, and team collaboration is not possible.