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AI Research Engineer with less than a year in Generative AI & Machine Learning
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 and Data Science Graduate with hands-on experience in Generative AI, Machine Learning, NLP, LLMs, and RAG. Skilled in Python, TensorFlow, PyTorch, Scikit-learn, prompt engineering, and AI application development. Experience building multi-agent and LLM-powered solutions with a strong foundation in machine learning, model evaluation, and problem solving.
Knowledge Institute of Technology
B.Tech · Artificial Intelligence and Data Science
August 1, 2021 – June 30, 2025
Wings Technocrats
AI Engineering Intern
August 1, 2023 – September 1, 2023
Salem, Tamil Nadu, India
Imagecon
Machine Learning Intern
June 1, 2023 – July 1, 2023
Salem, Tamil Nadu, India
Intelligent Document Retrieval and Querying System
June 1, 2026 – Present
Built an AI-powered document intelligence platform using Streamlit, Llama-3.3-70B-Instruct, and OpenRouter with a Retrieval-Augmented Generation (RAG) pipeline. Enabled natural language querying, real-time semantic indexing, and contextual response generation over uploaded Excel and CSV datasets, delivering an intelligent document exploration experience.
MedInsight AI – Intelligent Medical Report Analysis Agent
June 1, 2026 – Present
Engineered an AI-powered medical report analysis system using a dual-agent architecture an Analysis Agent for automated blood test PDF interpretation and a Chat Agent powered by RAG for contextual follow-up Q&A. Integrated multi-model LLM fallback via Groq to ensure high reliability, accurate health insight generation, and consistent performance across diverse report formats.
Machine Learning and Deep Learning
GUVI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internships demonstrate a strong interest and hands-on experience in cutting-edge AI domains like Generative AI, RAG, and multi-agent systems. This aligns well with a research-oriented role that values innovation and practical application of AI concepts. The diversity of projects, from document retrieval to medical report analysis and autonomous research assistants, shows adaptability and a broad interest within AI. The candidate's focus on AI and Data Science throughout their education and early career indicates a strong commitment to the field, which is a positive indicator for cultural fit in an AI research environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted AI systems, suggesting strong problem-solving and analytical skills. The use of multi-agent architectures and LLM fallbacks points to a thoughtful approach to system design and reliability. The internship experiences show practical application of theoretical knowledge and an ability to deliver functional systems. However, without specific psychometric or English test scores, it's difficult to assess communication clarity, work attitude, stress handling, or team collaboration directly. The project descriptions are clear and concise, indicating good written communication.