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AI Engineer with less than a year in Machine Learning, Deep Learning, NLP & Computer Vision
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Developer with experience in machine learning, deep learning, computer vision, and NLP. Skilled in building AI models using Python, FastAPI, and modern frameworks. Familiar with developing LLM-based applications using RAG and LangChain. Strong problem-solving mindset with interest in clean architecture and production-ready systems.
National University of Computer and Emerging Sciences
BS Computer Science · Computer Science
August 1, 2022 – June 30, 2026
Aspire College
Intermediate · Pre-Engineering
June 1, 2020 – May 31, 2022
Forest Monitoring System using LiDAR Point Cloud Analysis
January 1, 2024 – Present
Built forest monitoring pipeline using LiDAR 3D point clouds for tree detection, segmentation, and species classification. Implemented watershed segmentation, linear regression for DBH prediction, and Random Forest for species classification. Integrated tree tracking with biomass estimation and automated forestation/deforestation detection with heatmap visualization.
Skin Burn Classification System
January 1, 2024 – Present
Built real-time burn severity detection system classifying wounds into Degree 1, 2, and 3 using YOLOv8 with multi-class segmentation. Curated and annotated custom medical imaging dataset and fine-tuned YOLOv8 for clinical triage.
View ProjectMultilingual Video Subtitle Translation Pipeline
January 1, 2024 – Present
Built subtitle localization pipeline using Meta's NLLB model with audio transcription and automated SRT generation for 200+ languages. Enabled global video accessibility supporting multilingual content distribution at scale.
Research Paper Analysis Assistant (Reflection-RAG)
January 1, 2024 – Present
Built an AI assistant that answers questions from research papers using Retrieval-Augmented Generation (RAG). Added a self-review step to check and improve responses for better accuracy and reliability.
Cultural Fit Analysis
The candidate's project portfolio is diverse, covering medical, environmental, and language processing domains, which suggests adaptability and a broad interest in applying AI. The projects are primarily personal or academic, indicating self-motivation and initiative. The target role of 'AI Engineer' aligns well with the candidate's demonstrated skills and project focus on building AI models and applications. However, the lack of professional experience means cultural fit in a corporate environment is yet to be fully proven.
Soft Skills & Operational Fit
The candidate's resume highlights a 'strong problem-solving mindset' and an interest in 'clean architecture and production-ready systems'. The project descriptions are clear and demonstrate an ability to work on complex, multi-faceted problems. However, without specific psychometric test results or interview data, it's difficult to fully assess soft skills like teamwork, stress handling, or direct communication clarity in a professional setting.