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Software Engineer with less than a year in ML, Backend, and AI Systems
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Software Engineer with a focus on Machine Learning and backend systems, experienced in transforming ML models into production-ready applications. Strong background in building complete ML pipelines using Python and scikit-learn, from data preprocessing to model evaluation. Capable of deploying and serving these models via modern frameworks like FastAPI, enabling scalable and user-facing solutions. Comfortable handling real-world data and building reproducible, maintainable systems.
Punjab University College of Information and Technology (PUCIT)
Bachelor of Science · Computer Science (BSCS)
September 1, 2023 – Present
Autonomous Cricket Highlight Generator
September 1, 2023 – Present
Engineered an autonomous machine learning pipeline to extract high-impact cricket highlights entirely without human intervention, fusing parallel video, audio, and text data streams from raw broadcast feeds. Architected a multimodal event detection system that aligns Cricsheet metadata with on-screen EasyOCR readings, validating exciting moments by analyzing raw audio spikes (Librosa) and commentary sentiment (OpenAI Whisper + Logistic Regression). Built a synchronization engine to correct broadcast delay, utilizing FFmpeg to dynamically trim precisely buffered video clips. Experimented with YOLOv8 object detection to calculate visual action scores via player density and clustering.
Content-Based Movie Recommendation System
September 1, 2023 – Present
Built a content-based recommendation engine using NLP on movie metadata (genres, keywords, cast, crew). Preprocessed data by parsing nested JSON and applying Bag-of-Words vectorization (scikit-learn). Used cosine similarity to generate movie recommendations from feature vectors. Developed an interactive Streamlit interface with API integration for real-time results.
View ProjectMNIST Digit Classification
September 1, 2023 – Present
Trained and compared SGD and Random Forest models for MNIST multiclass image classification. Assessed models using advanced metrics like Confusion Matrices, Precision/Recall, F1-scores, and ROC AUC.
Autonomous Data Analyst AI System
September 1, 2023 – Present
Integrated Gemini LLMs with a TF-IDF RAG system and Pandas ingestion pipeline to translate natural language queries into automated analysis across CSV, SQL, and PDF datasets. Executed AI-generated Python code safely within a secure, regex-validated sandbox. Engineered an autonomous self-healing loop for automated debugging and code correction.
View ProjectCalifornian Housing Price Prediction
September 1, 2023 – Present
Built a comprehensive Scikit-Learn ML pipeline featuring custom data imputation and robust feature scaling. Trained a predictive Random Forest regression model, systematically optimizing core hyperparameters via GridSearchCV. Rigorously evaluated final model generalization performance utilizing k-fold cross-validation and baseline RMSE metrics.
Other Python Projects
September 1, 2023 – Present
Built a Django web application integrating a deployed Random Forest inference pipeline for real-time glass classification. Developed a full-stack Django blogging app featuring user authentication, media uploads, and an admin moderation panel. Created a console-based social media app using OOP for account management, post handling, and engagement analytics. Programmed an event-driven Snake Game using Tkinter with real-time collision detection and state management. Built an interactive voice assistant using SpeechRecognition and text-to-speech for real-time task automation.
Resume Analyzer System
September 1, 2023 – Present
Developed a Resume Analyzer for resume screening and job description matching using TF-IDF and Cosine Similarity. Built an NLP pipeline for PDF/DOCX resume parsing, skill extraction, and keyword analysis. Implemented regex and dictionary-based skill matching to identify missing job-relevant skills. Deployed the application using FastAPI for real-time ATS-style resume evaluation.
Cultural Fit Analysis
The candidate's portfolio showcases a strong passion for AI/ML and backend development, aligning well with a Software Engineer role focused on these areas. The diversity of projects, from cricket highlight generation to movie recommendations and resume analysis, indicates a broad interest and ability to apply technical skills to various domains. The use of modern frameworks and tools suggests an adaptability to current industry practices. However, the lack of team-based projects or open-source contributions makes it difficult to assess collaboration and broader cultural fit beyond individual technical drive.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations. The self-healing loop and secure sandbox in the 'Autonomous Data Analyst AI System' project suggest an attention to robustness and security. The diverse range of personal projects indicates initiative and a proactive learning attitude. However, without formal work experience, the candidate's ability to operate within a team, handle stress, or manage project timelines in a professional setting is unproven.