Generative AI Engineer with less than a year in NLP & Deep 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
Computer Science postgraduate skilled in ML, NLP, Deep Learning, and multimodal AI systems. Experienced in building academic and personal end-to-end ML projects involving RAG, embeddings, feature engineering, and model deployment. Strong foundation in statistics, data analysis, and Python-based ML pipelines, with hands-on practice using Streamlit, vector databases, and LLM integrations. Seeking an opportunity to apply data-driven problem-solving skills to real-world challenges.
National Institute of Technology, Tiruchirappalli
Masters of Science · Computer Science
August 1, 2024 – June 1, 2026
Patna Science College, Patna
Bachelor of Science · Statistics
July 1, 2021 – June 1, 2024
NIT, Trichy
Data Science Intern
May 1, 2025 – July 1, 2025
Tamil Nadu, India
GenAI Career Assistant – Multi-Agent AI Mentor
April 1, 2026 – Present
Built an AI-powered assistant for Generative AI learning, resume building, interview preparation, and job search using LangChain, LangGraph, and Google Gemini LLM. Implemented multi-agent workflows and AI-driven conversation loops to provide personalized, real-time, and interactive career guidance.
View ProjectSpeech Emotion Recognition Using Deep Learning
March 1, 2026 – Present
Developed a system to classify emotional states from audio using MFCC features, waveform and spectrogram analysis, and normalization. Designed and trained a CNN+BiLSTM model with dropout, achieving 96% validation accuracy for emotion classification. Built a custom prediction pipeline for real-time analysis of new audio recordings.
View ProjectE-commerce Shipment Delay Prediction
February 1, 2026 – Present
Developed ML models to predict shipment delays (~40% delay rate) using features such as product discounts and weight. Implemented and compared Logistic Regression, KNN, Random Forest, XGBoost, and Decision Tree, achieving 91.55% accuracy with Decision Tree after hyperparameter tuning. Delivered actionable insights to improve supply chain performance and reduce delays.
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in cutting-edge AI technologies, particularly Generative AI and multi-agent systems, which aligns well with a Generative AI Engineer role. The diversity of projects (career assistant, emotion recognition, shipment prediction) shows a broad application of ML/DL skills. The academic achievements and positions of responsibility indicate a proactive and engaged individual. However, the lack of professional experience beyond a single internship means cultural fit in a corporate environment is less proven.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems and deliver actionable insights. Roles as Class Representative and Hostel Representative suggest leadership and coordination skills. However, the resume does not provide explicit details on teamwork, problem-solving methodologies, or adaptability in a professional setting beyond academic projects and a short internship.