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AI Engineer with less than a year in machine learning, deep learning & NLP.
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Assessing your cultural and operational fit
AI/ML-focused Computer Science undergraduate with hands-on experience in machine learning, deep learning, NLP, and computer vision. Proficient in building end-to-end ML pipelines, training and evaluating classification models, and deploying interactive applications using Python, TensorFlow, Scikit-learn. Experienced with feature engineering, data preprocessing, model optimisation, and experiment tracking via MLflow.
Sharda University
Bachelor of Technology · Computer Science
August 1, 2023 – Present
Sharda University
AI/ML Trainee
May 1, 2025 – June 1, 2025
Greater Noida, Uttar Pradesh, India
AI Resume Screening System
April 1, 2026 – April 1, 2026
Developed an AI-powered resume screening tool for automated candidate analysis. Implemented NLP pipelines, TF-IDF vectorization and keyword extraction for automated candidate shortlisting. Built a TF-IDF resume classifier with 85% accuracy for role matching. Designed a Streamlit dashboard for resume upload and feedback generation.
Credit Card Fraud Detection with MLflow
September 1, 2025 – September 1, 2025
Built an end-to-end fraud detection pipeline using Random Forest, Gradient Boosting, and Neural Networks. Performed feature engineering, preprocessing, and model comparison to optimize fraud classification accuracy. Implemented MLflow-based experiment tracking and model monitoring for scalable machine learning workflows.
Emotion Recognition System
October 1, 2024 – October 1, 2024
Developed a CNN-based facial emotion detection system with 80%+ accuracy. Executed real-time emotion detection using webcam input and optimized performance. Improved model generalization through data augmentation and dropout regularization.
Google Cloud AI/ML Learning Path
Google Cloud Skills Boost
January 1, 2025 – Present
Generative AI & Large Language Models
Microsoft Learn
January 1, 2025 – Present
Data Science with Python
EDUCBA
January 1, 2024 – Present
Machine Learning Fundamentals
Microsoft Learn
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's academic projects and hackathon participation show a strong interest in applying AI/ML to diverse problems, from emotion recognition to fraud detection and resume screening. This breadth of application, combined with certifications in Generative AI and Google Cloud AI/ML, indicates a proactive learning attitude and alignment with an innovative, AI-focused culture. The academic nature of all projects and limited professional experience suggest a need for mentorship and integration into a professional team environment.
Soft Skills & Operational Fit
The candidate demonstrates analytical thinking and problem-solving skills through their project work and DSA practice. Their involvement in hackathons suggests a collaborative and innovative mindset. The focus on building practical applications indicates a results-oriented approach. However, the lack of professional experience beyond an internship means operational fit in a fast-paced, senior environment is yet to be fully proven.