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AI Engineer with less than a year in Python, LLMs, and RAG systems.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI/ML enthusiast with hands-on experience in Python, LLMs, and RAG systems. Built scalable AI platforms with FastAPI, LangChain, and Docker, demonstrating strong problem-solving and analytical skills.
Vardhaman College of Engineering
B.Tech · Computer Science Engineering
August 1, 2024 – June 30, 2027
VMR College
Diploma · Computer Science
August 1, 2021 – June 30, 2024
Micro Information Technology Services
Python Development Trainee
May 1, 2024 – June 1, 2024
India
JobRadar AI Fraud Intelligence Platform
June 1, 2024 – Present
Collected and preprocessed job posting datasets, addressing 95:5 class imbalance using weighted CrossEntropyLoss to enhance model analytical performance; Fine-tuned DistilBERT for binary fraud classification, achieving F1: 0.89, PR-AUC: 0.93, and MCC: 0.86 through iterative problem-solving and performance analysis; Deployed FastAPI backend on Hugging Face Spaces with Streamlit dashboard, enabling batch prediction API for 50+ postings per call
DocMind Full-Stack RAG Document Intelligence Platform
June 1, 2024 – Present
Developed a scalable RAG platform solving document intelligence challenges by enabling semantic search and context-grounded Q&A for 500+ users, demonstrating strong problem-solving skills; Implemented hybrid retrieval (dense + BM25 sparse) with user-scoped FAISS indices, improving recall by 30% through analytical optimization of embedding strategies; Built FastAPI backend with JWT OAuth2 authentication and streaming Q&A via SSE using Groq API (Llama-3.1-8B), ensuring secure and real-time user interactions; Containerized the application with Docker and Docker Compose, deployed on Hugging Face Spaces and Vercel for seamless scalability and maintenance
Machine Learning
Infosys Springboard
May 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects showcase a proactive and self-driven approach to learning and applying AI/ML concepts. The diversity of projects (fraud detection, document intelligence) and the use of various modern tools (FastAPI, Docker, Hugging Face Spaces, Vercel) indicate an eagerness to explore and implement new technologies. The competitive programming background suggests a results-oriented mindset. The candidate's profile aligns well with an innovative and fast-paced AI engineering environment, though the lack of professional experience beyond a short internship means cultural fit is primarily inferred from personal initiative.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving and analytical skills through project descriptions, particularly in optimizing model performance and retrieval strategies. Collaboration and technical communication are mentioned during the internship, indicating a foundational understanding of teamwork. The competitive programming achievements suggest a strong aptitude for logical reasoning and persistence.