Greater Delhi Area
As an ECE (AI-ML) undergraduate at NSUT Delhi, I specialize in combining software engineering and artificial intelligence with financial analytics. I am highly motivated by the challenge of using code to parse complex data and solve real-world problems within the financial markets. I recently joined WorldQuant , gaining hands-on exposure to the quantitative finance and hedge fund industry. This role allows me to apply my rigorous foundation in Python and Data Structures & Algorithms to financial modeling and algorithmic strategy development. Previously, I developed Generative AI and RAG architectures at Siemens Energy and conducted in-depth security assessments at NCFL-IFSO. These experiences have equipped me with a strong command of scalable backend systems, vector databases, and secure coding practices—skills I now leverage in quantitative research. Technical Stack & Interests: Python, GenAI & LLMs, Full-Stack Development, Algorithmic Problem Solving, Financial Technologies, and Quantitative Finance. I am always open to connecting with professionals in FinTech, High-Frequency Trading (HFT), and AI development. https://www.naukri.com/code360/profile/54af89e6-6cc5-4f8f-8586-2e475e2adca5
AI Skills & Project Success This internship was an intensive dive into Generative AI. I gained practical expertise in: RAG (Retrieval Augmented Generation) & Fine-tuning. Generative AI, Automation, and LLM fundamentals, architecture, & capabilities. GPT Prompt Engineering & Azure OpenAI solutions. Vector Database integration (how LLMs use them for enhanced retrieval) and concepts like Embeddings & Semantic Chunking. The pinnacle was developing a Medical Assisting Chatbot PoC. Its mission: accurate medical info strictly from documents via a robust RAG pipeline. After tackling initial API key and LLM selection hurdles, we successfully integrated the Google Gemini API. Thrilled to confirm this project was approved by my manager and mentors! Tech Used Frontend: HTML, CSS, JavaScript. Backend: Python (Flask) for file processing, vector DB interaction, and Google Gemini API calls. Generative AI Config: Python backend for embedding models, vector storage, and RAG context retrieval.
Intelligence Fusion And Strategic Operations, Special Cell, Delhi Police, December 2024 - January 2025 Conducted Android vulnerability assessments using the tool ADB. Identified security loopholes, simulated attacks, and proposed mitigation strategies. Prepared detailed vulnerability reports and contributed to secure coding practices. Gained experience in mobile forensics and cybersecurity protocols.
Event management, co-ordination