AI Engineer with 1+ years in Machine Learning & NLP
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Aspiring AI/ML Engineer and Data Science student with hands-on experience building LLM-powered applications, RAG pipelines, and multi-agent AI systems using LangChain, LangGraph, and OpenAI APIs. Skilled in Python, FastAPI, NLP, Reinforcement Learning, and vector databases (ChromaDB, FAISS). Published researcher in uncertainty-aware interpretable AI and adaptive graph learning. Passionate about transforming cutting-edge AI research into reliable, impactful real-world solutions.
Amrita Vishwa Vidyapeetham
Integrated M.Sc. · Data Science
August 1, 2022 – June 30, 2027
Shree Sarasswathi Vidhyaah Mandheer
Higher Secondary Education (CBSE)
June 1, 2020 – May 31, 2022
Helyxon Healthcare Private Limited
AI Intern
September 1, 2025 – February 1, 2026
India
Pricol Limited
Data Science Intern
May 1, 2025 – June 1, 2025
India
Multi-Agent AI Career Development Ecosystem
June 1, 2026 – Present
Built an LLM-powered multi-agent career intelligence platform (FastAPI + React) with Profiler, Market Scout, Strategist, Scheduler, and Chat agents. Implemented structured JSON outputs, ChromaDB semantic memory, async SQLAlchemy persistence, and integrations for PDF resume parsing, GitHub profile analysis, and roadmap/schedule generation. Concepts: Multi-agent orchestration, RAG-style memory, skill gap analysis, roadmap generation, skill radar chart dashboard.
AI Copilot for Financial Summarization & Risk Analysis
June 1, 2026 – Present
Built an AI-powered financial research copilot for document summarization, sentiment analysis, and risk flagging using RAG with semantic verification to reduce hallucinations. Combined NLP insights with technical indicators (SMA, RSI, Bollinger Bands) and produced explainable trading-style insights with evidence and safety disclaimers. End-to-end pipeline: document ingestion, chunking, retrieval, summarization, sentiment/emotion analysis, price indicator fusion, and hallucination verification.
Smart Home HVAC Optimization
June 1, 2026 – Present
Developed an AI-driven HVAC energy optimization system using PPO-based deep reinforcement learning and CityLearn, integrating real-time weather data and custom reward engineering. Achieved 15%+ reduction in simulated energy consumption while maintaining thermal comfort targets with stable policy convergence.
Stock Trading Bot Multi-Agent Reinforcement Learning
June 1, 2026 – Present
Built a multi-agent deep RL trading framework implementing DQN, PPO, SAC, and Random Forest baseline models across discrete and continuous action spaces using 5+ years of historical market data. Designed a custom evaluation suite with 6+ financial metrics including cumulative returns, Sharpe ratio, and maximum drawdown to compare agent performance across training regimes.
Google Data Analytics
Coursera
June 1, 2026 – Present
AWS Cloud Practitioner
Amrita Vishwa Vidyapeetham
June 1, 2026 – Present
Machine Learning
Teachnook
June 1, 2026 – Present
Python Foundation
Infosys Springboard
June 1, 2026 – Present
Business Communication
Infosys Springboard
June 1, 2026 – Present
Problem Solving and Coding
Amrita Vishwa Vidyapeetham
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse range of personal projects (career development ecosystem, financial copilot, HVAC optimization, trading bot) demonstrates a broad interest in applying AI across different domains. The internships, though short, show exposure to industry settings. The target role of 'AI Engineer' aligns well with the candidate's demonstrated skills and project focus. The breadth of technologies and concepts explored indicates a curious and adaptable mindset, which is generally positive for cultural fit in an innovative environment. However, the psychometric test score is a concern for cultural fit, as it might indicate challenges in areas like teamwork or stress management.
Soft Skills & Operational Fit
The candidate's project descriptions and experience indicate a proactive and problem-solving attitude, with a focus on building practical AI solutions. The psychometric test score (206/500) suggests potential areas for development in logical reasoning, work attitude, stress handling, or team collaboration, which could impact operational fit. However, the detailed project work shows initiative and the ability to execute complex tasks.