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AI Engineer with less than a year in NLP and Generative AI applications
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring AI/ML Engineer with a strong foundation in Python, Machine Learning, Natural Language Processing, and Generative AI. Experienced in building NLP-based applications, RAG-powered chatbots, and transformer-based language models. Skilled in Scikit-learn, TensorFlow, PyTorch, Pandas, and vector databases, with a strong interest in developing intelligent, scalable AI solutions.
Women's Christian College
MSc Information Technology · Information Technology
August 1, 2023 – June 30, 2025
Ethiraj College for Women
Bachelor of Computer Science (BSc) · Computer Science
August 1, 2020 – June 30, 2023
Crop Recommendation System
June 1, 2026 – June 1, 2026
Built a machine learning-based crop recommendation system using Scikit-learn. Processed soil and climate data using Pandas and NumPy for model training. Developed a web-integrated solution for prediction support.
RAG-based Document Question Answering Chatbot
June 1, 2025 – September 1, 2025
Developed a Retrieval-Augmented Generation (RAG) chatbot to answer questions from large documents of up to 1000 pages. Implemented document chunking, embedding generation, and vector database storage for efficient retrieval. Used cosine similarity search to return context-aware and accurate responses. Built an NLP-based question answering pipeline using retrieval and generation techniques.
AI-Based Language Translation System
January 1, 2025 – April 1, 2025
Built a French-to-English language translation system using the MarianMT Transformer model. Preprocessed text using word and sentence tokenization to improve translation quality. Applied NLP techniques for multilingual text handling and model-based translation.
Introduction to Programming using Python
Digilabs
June 1, 2026 – Present
Artificial Intelligence Primer Certification
Infosys Springboard
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects show a strong interest in AI/ML applications, aligning well with an AI Engineer role. The diversity of projects (RAG chatbot, language translation, crop recommendation) indicates a broad interest in applying AI across different domains. The academic background and certifications suggest a proactive learning attitude. However, the lack of professional experience means there's no data to assess fit within a corporate culture or experience with industry-standard development workflows.
Soft Skills & Operational Fit
The candidate's academic projects demonstrate problem-solving skills and an ability to apply theoretical knowledge to practical scenarios. The hackathon participation suggests teamwork and innovation. However, without professional experience or specific behavioral assessments, it is difficult to fully assess operational fit, stress handling, or advanced team collaboration skills.