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AI Research Engineer with less than a year in AI/ML & NLP
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 Intern with experience in developing and training machine learning and deep learning models for real-world applications. Proven ability to improve predictive performance through systematic experimentation, data preprocessing, feature engineering, and model evaluation. Skilled in exploring Generative AI techniques and optimizing model performance metrics through iterative tuning and validation strategies. Passionate about reducing model error rates by implementing structured testing, hyperparameter optimization, and performance monitoring practices.
Heritage Institute of Technology
B.Tech · Computer Science & Engineering (AI & ML)
August 1, 2023 – June 30, 2026
Silli Polytechnic
Diploma · Electrical Engineering
August 1, 2022 – June 30, 2022
Rainbow Public School
Matriculation · General Studies
N/A – Present
Ardent Computech Pvt. Ltd.
AI/ML Intern
June 1, 2025 – July 31, 2025
India
Brain Tumor Detection System (CNN-Based)
June 24, 2026 – Present
Built a deep learning solution using Convolutional Neural Networks (CNNs) for MRI image classification and tumor detection. Achieved 90% classification accuracy and a Dice Coefficient of 0.85 on the BraTS validation dataset. Deployed the application using FastAPI and Streamlit to enable real-time inference and interactive prediction workflows.
Intelligent Text Summarizer (NLP + Transformers)
June 24, 2026 – Present
Developed a hybrid text summarization system leveraging TextRank and transformer-based models including BART and T5. Achieved a ROUGE-1 score of 0.47 on benchmark datasets for automated summary evaluation. Implemented TF-IDF feature extraction, clustering algorithms, and evaluation pipelines to improve summarization quality.
AI Research Assistant (RAG-Based System)
June 24, 2026 – Present
Designed and implemented a Retrieval-Augmented Generation (RAG) architecture utilizing more than 420 research papers. Achieved 95% retrieval precision while reducing query response time to 0.3 seconds. Built a scalable multi-domain research assistance pipeline integrating LLMs and vector-based retrieval mechanisms.
Machine Learning A-Z: AI, Python & R
Coursera
January 1, 2025 – Present
Certified Python Programming Associate
Unknown
January 1, 2025 – Present
J.P. Morgan Software Engineering Virtual Experience
Forage
January 1, 2024 – Present
Tata Data Visualization Job Simulation
Forage
January 1, 2024 – Present
The candidate scored 94% on the 'Data Scientist — Artificial Intelligence' test, indicating a very strong grasp of the subject matter and related skills.
Strengths
Limitations
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and initiative in cutting-edge AI/ML domains (RAG, CNNs, Transformers). The internship experience, though short, aligns well with the target role's requirements for model development and optimization. The breadth of skills and project diversity (NLP, Computer Vision, Generative AI) indicates adaptability and a proactive learning attitude, which are positive indicators for cultural fit in a research-oriented environment. However, the experience is primarily academic, and exposure to diverse team structures or large-scale enterprise environments is limited.
Soft Skills & Operational Fit
The psychometric test score of 359/500 suggests a moderate fit in areas like logical reasoning, work attitude, stress handling, and team collaboration. While not exceptionally high, it indicates a baseline capability. The English test score of 84/100 shows good communication clarity and professional language usage, which is crucial for research and collaboration.