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AI Engineer with less than a year in Computer Vision & LLM-based systems
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Assessing your cultural and operational fit
AI/ML engineer with hands-on experience in Computer Vision and LLM-based systems, focusing on building end-to-end AI pipelines from data preprocessing to deployment. Experienced in RAG pipelines, real-time CV systems, applied deep learning and Agentic AI. Comfortable working in Linux environments, integrating APIs, and optimizing inference pipelines. Seeking to contribute to production-grade AI solutions in CV and LLM domains.
GLA University
B.Tech · Computer Science (AI & ML)
August 1, 2022 – June 30, 2026
Romex International
Intermediate
June 1, 2021 – May 31, 2022
Dr.R.M.SAHA Gloabl School
High School
June 1, 2019 – May 31, 2020
GLA University
AI Trainee
June 1, 2024 – July 1, 2024
India
Abroad Pathway Immigration Consultant Pvt. Ltd.
Python Intern
November 1, 2023 – December 1, 2023
Delhi, Delhi, India
DocuMind AI: Retrieval-Augmented Knowledge Intelligence System
June 1, 2026 – Present
Developed an LLM-powered RAG system for context-aware question answering over custom document collections. Built a document ingestion pipeline with chunking and embedding-based retrieval for efficient knowledge access. Designed a modular retrieval-generation architecture using DSPy and improved response relevance through prompt and retrieval optimisation.
IntelliVision: Real-Time Multi-Object Tracking & Event Detection Platform
June 1, 2026 – Present
Built a real-time multi-object detection and tracking system using YOLOv8 and DeepSORT to analyze live video streams and identify human activity and motion events. • Implemented automated event-based logging with time-stamped video clips and snapshots for surveillance and monitoring use cases. Optimised the inference pipeline for low-latency real-time performance in smart environment scenarios.
AgroSmart AI: Predictive Irrigation & Water Optimization System
June 1, 2026 – Present
Developed an AI-driven irrigation control system using sensor data and ML-based predictions to support precision farming. • Automated watering decisions based on soil moisture and environmental conditions for efficient resource usage. Implemented predictive scheduling and real-time IoT sensor integration to reduce water wastage.
Rabbit AI Hackathon
Unknown
June 1, 2026 – Present
IBM Ice Day Solvathon
IBM
June 1, 2026 – Present
Smart India Hackathon (Internal Round)
Unknown
June 1, 2026 – Present
NSS Society, GLA University
GLA University
June 1, 2026 – Present
Predicting Telecom Customer Churn with Combined Machine Learning Models
ETCom 2025 IEEE Conference
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and foundational skill set in AI/ML, aligning well with an AI Engineer role. Participation in hackathons and a research paper indicates a proactive and competitive spirit. The diversity of projects (object tracking, RAG, predictive irrigation) shows a broad interest in AI applications. However, the experience is primarily academic and internship-based, which might require mentorship in a professional, fast-paced environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex technical problems and optimize solutions. Collaboration is mentioned in one internship, suggesting teamwork skills. However, the provided data is insufficient to fully assess other soft skills like leadership, problem-solving under pressure, or detailed operational fit beyond technical execution.