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Software Engineer with less than a year in Machine Learning & Cloud Technologies.
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Highly motivated and results-oriented Software Engineer Intern with 3 months of experience specializing in Machine Learning, Cloud Services (Microsoft Azure), and data management. Proven ability to develop and deploy ML models (CNN, SVM, Random Forest, Logistic Regression), implement complex algorithms (Dijkstra's, BFS, CPU Scheduling), and optimize data accessibility for large-scale systems. Strong proficiency in Python, C++, SQL, and cloud platforms, demonstrated through impactful projects and an internship at Mitchtek Professional Inc.
IIT Bombay
Bachelor of Technology · Computer Science & Engineering
August 1, 2021 – June 30, 2025
Mitchtek Professional Inc.
Software Engineer, Intern
May 1, 2024 – July 1, 2024
Los Angeles, California, United States
Delhi Metro Navigation Application
July 1, 2024 – August 1, 2024
Engineered a C++ application, finding shortest route between metro stations using Dijkstra's & BFS algorithm. Integrated multi-line, color-coded station support, futher enhancing clarity & user experience across 200+ stations. Incoporated robust error handling and validation mechanisms to manage incorrect inputs and edge cases effectively.
CPU Scheduling Algorithms - Operating System
June 1, 2024 – July 1, 2024
Implemented a diverse set of CPU scheduling algorithms in C++ to effectively manage process scheduling. Utilized methods such as First Come First Serve, Round Robin, Shortest Remaining Time, and Shortest Process Next. Developed algorithms including Highest Response Ratio Next and Feedback to enhance CPU scheduling efficiency.
IPL Data Analysis & Prediction Models
January 1, 2024 – May 1, 2024
Performed Exploratory Data Analysis on IPL dataset in Python and gained useful insights for feature selection. Trained Random Forest, SVM, Neural Network, and Decision Tree models to predict final scores and match outcomes. Developed forecasting models with accuracy of 80.3% in score prediction and about 85.7% in winner prediction.
Music Genre Classification
January 1, 2024 – May 1, 2024
Developed music genre classifier using K-Means & CNN models, accurately predict genres from Spotify audio data. Implemented advanced clustering techniques to discover 10+ synthetic genres, enhancing identification accuracy. Enhanced model interpretability by identifying key audio features, achieving around 80% accuracy for synthetic genre. Achieved 93% accuracy with a carefully fine-tuned CNN model for accurate and highly efficient genre classification.
Credit Card Fraud Detection Using ML
May 1, 2023 – June 1, 2023
Employed t-SNE and PCA algorithms to gain insights into high-dimensional data and interpret complex patterns. Used different algorithms Logistic Regression, KNN, SVC and Decision Tree Classifier to train the model. Achieved exceptional results using Logistic Regression with an accuracy score of 0.962 and an F-1 score of 0.95.
Awarded with perfectAA (10/10) grade in 10+ courses for extraordinary academic proficiency in the course
IIT Bombay
January 1, 2024 – Present
Ranked in top 2.8 percentile IIT-JEE Advanced of 0.13 M+ & top 2.3 percentile JEE Main of 1.1 M+ candidates
IIT-JEE
January 1, 2021 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in diverse areas of computer science, including machine learning, operating systems, and data analysis. The internship at Mitchtek Professional Inc. shows an ability to adapt to a professional environment and contribute to real-world applications. The breadth of technologies used across projects (C++, Python, various ML libraries, SQL, Azure) indicates a willingness to learn and apply new skills. The academic excellence suggests a driven and high-achieving individual, which generally aligns well with a performance-oriented culture. However, the lack of non-academic or team-based projects limits the assessment of collaboration and broader cultural alignment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems, manage data, and implement algorithms. The internship experience suggests an understanding of deployment and optimization in a cloud environment. The academic achievements highlight a strong work ethic and problem-solving aptitude. However, without direct assessment data for soft skills, a comprehensive evaluation of operational fit, teamwork, and communication style is limited.