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Machine Learning Engineer with less than a year in Python & 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
Enthusiastic Machine Learning Engineer skilled in developing predictive and optimization models using Python, Scikit-learn, TensorFlow, and PyTorch. Experienced in building data-driven solutions and fine-tuning deep learning models for real-world applications. Seeking to contribute to software or ML engineering teams through innovation and analytical problem-solving.
INDIAN INSTITUTE OF INFORMATION TECHNOLOGY VADODARA
B-Tech · Computer Science and Engineering
November 1, 2022 – June 1, 2026
NIT Tiruchirappalli
INTERN AT NIT Tiruchirappalli - Machine Learning
May 1, 2025 – June 1, 2025
India
Sentiment-Analysis using Tweets
June 19, 2026 – Present
Developed a BERT-based transformer model to classify tweets as positive, neutral, or negative. Implemented text preprocessing and data augmentation to improve model robustness. Fine-tuned the model using PyTorch and Hugging Face Transformers with optimized training strategies. Achieved high classification accuracy through early stopping and hyperparameter tuning.
View ProjectAI-Powered Pneumonia Detection from Chest X-Ray Images
June 19, 2026 – Present
Built pneumonia detection AI with 95%+ accuracy using DenseNet121 and TensorFlow on 5,800+ chest X-rays Implemented explainable AI with Grad-CAM visualization for medical model interpretability Developed complete ML pipeline with data preprocessing, model training, and comprehensive evaluation Achieved production-ready performance with precision >96% and recall >94% for clinical applications
View ProjectCultural Fit Analysis
The candidate's projects demonstrate a strong interest in applying machine learning to diverse problems (medical imaging, sentiment analysis), which aligns well with an innovative and problem-solving culture. The involvement in a photography club suggests interests beyond core academics, potentially indicating a well-rounded individual. However, the limited professional experience and academic stage mean that cultural fit is primarily inferred from project choices and stated skills rather than extensive professional interactions.
Soft Skills & Operational Fit
The candidate's internship experience at NIT Tiruchirappalli highlights collaboration with a research-oriented team, problem-solving, and iterative testing, indicating a good operational fit for roles requiring teamwork and continuous improvement. Project documentation skills are also noted. However, without specific psychometric test results, a deeper assessment of work attitude, stress handling, and team collaboration is not possible.