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Machine Learning Engineer with less than a year in NLP/LLM engineering, computer vision, and full-st
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Data Scientist and AI Developer with extensive experience in NLP/LLM engineering and computer vision. Skilled in designing automated pipelines and agentic workflows to solve complex operational challenges. Hands-on experience migrating legacy models to modern cloud spaces and resolving integration hurdles in production environments. Committed to developing innovative, data-driven products that utilize cutting-edge deep learning frameworks and automation protocols.
NIT Hamirpur
M.Sc. · Mathematics & Computing
January 1, 2025 – Present
Maharaja Ganga Singh University
B.Sc. · PCM
January 1, 2020 – January 1, 2023
Agentic Job Application Pipeline
June 1, 2025 – Present
Built an end-to-end autonomous pipeline targeting LinkedIn and Naukri, automating job discovery, resume-JD semantic matching, and one-click application submission. Implemented semantic similarity scoring using Ollama-embedded local LLMs for resume-JD relevance ranking. Orchestrated multi-step agentic workflows via LangGraph with Playwright-driven browser automation and anti-detection capabilities. Developed a Streamlit-based real-time tracking dashboard with persistent application state monitoring.
View ProjectFraud Shield - Deployed ML-Driven Fraud Detection System
June 1, 2025 – Present
Engineered an end-to-end fraud detection system featuring a FastAPI backend (deployed on Hugging Face Spaces) and a React frontend (deployed on Vercel). Integrated high-performance XGBoost and TensorFlow models to provide real-time risk scoring and mitigate fraudulent transactions with high precision. Developed an interactive dashboard for live monitoring and feature-level explainability, bridging the gap between complex ML outputs and actionable business insights.
Full-Stack Web Applications – Luminary | Wipsom | Top Avenue
June 1, 2025 – Present
Luminary: developed a production-grade social platform with real-time chat (Socket.io), JWT authentication on Next.js 14 and Express. Wipsom: engineered a full-featured e-commerce and productivity platform with end-to-end user flows. Top Avenue: designed and deployed a responsive, full-stack web application tailored for hospitality, streamlining user interactions and digital workflows.
Automated YouTube Content Pipeline - Local LLM System
June 1, 2025 – Present
Engineered an 8-agent autonomous system that handles trend research, script generation, voiceovers, visual asset fetching, and full video assembly without human intervention. Optimised architecture for a 6 GB VRAM GPU by stripping heavy abstractions, implementing strict GPU garbage collection, and using native FFmpeg subprocesses for crash-free rendering. Built a real-time management dashboard with persistent state recovery using FastAPI backend and SQLite state management. Integrated Groq LLM for fast inference, local OpenAI Whisper for transcription, and edge-tts for neural voiceover generation.
Plant Disease Detection System
June 1, 2025 – Present
Designed and trained a CNN-based image classification model to detect plant diseases from leaf images using labeled datasets with preprocessing and data augmentation techniques. Achieved strong multi-class classification performance across multiple disease categories with optimised model architecture. Deployed the model as an interactive Streamlit web application, enabling users to upload leaf images and receive real-time disease predictions.
View ProjectMachine Learning Specialization
Andrew Ng Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's portfolio showcases a strong passion for AI/ML and automation, aligning well with an innovative and fast-paced technical culture. The diversity of personal projects, from plant disease detection to autonomous content pipelines and job application systems, indicates a broad interest in applying ML to various real-world problems. The ongoing M.Sc. in Mathematics & Computing further supports a commitment to continuous learning and academic rigor. The lack of professional experience makes it challenging to assess cultural fit beyond technical alignment.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations and a proactive approach to learning new technologies. The focus on autonomous systems and optimized architectures suggests an independent and efficient work style. However, without direct work experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or communication clarity in a professional setting.