Help & Supportcareers@gravityer.com
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 Engineer with less than a year in Machine Learning, Deep Learning, and Generative AI, eager to ap
Artificial Intelligence undergraduate with strong expertise in Machine Learning, Deep Learning, Generative Al, and intelligent software systems. Developed Al-powered applications involving semantic search, NLP, sentiment analysis, biomedical data processing, automation, and real-time systems. Skilled in Python development, vector databases, embeddings, and modern Al workflows including Generative Al and Agentic Al concepts. Hands-on experience building deep learning models, intelligent retrieval systems, and scalable applications using TensorFlow, Hugging Face, FAISS, Flask, and Streamlit. Strong foundation in data structures, object oriented programming, databases, APIs, and software engineering principles with a passion for solving real-world problems through Al-driven solutions.
Air University
Bachelor's of Science in Artificial Intelligence · Artificial Intelligence
January 1, 2023 – January 1, 2027
Real Estate Database Management System
January 1, 2026 – Present
Built a desktop-based system for managing rental properties, tenants, and payment records.
Deepfake Video Detection Using EfficientNet and LSTM
January 1, 2026 – Present
Developed a deep learning-based video classification system for detecting deepfakes using the DFD / FaceForensics++ dataset (763 videos) with real vs manipulated samples. Built a full video preprocessing pipeline including face detection, frame extraction, uniform sampling (16 frames per video), and resizing to 224x224 for model input. Extracted spatial features using pretrained EfficientNet (1280-dim embeddings per frame) and constructed temporal sequences for each video. Designed and trained an EfficientNet + LSTM hybrid architecture to capture spatial artifacts and temporal inconsistencies in facial motion. Achieved strong performance with up to 97% test accuracy.
AI Research & Automation Agent (Agentic RAG System)
January 1, 2026 – Present
Built an AI-powered research assistant using LangChain and LangGraph to handle multi-step workflows such as search, data extraction, retrieval, and summarization. Implemented a RAG system using FAISS vector database and embeddings (OpenAI/Sentence-BERT) for storing and retrieving relevant context. Used SerpAPI along with BeautifulSoup and Selenium to collect and process information from multiple web sources. Integrated LLMs (GPT / Llama) for summarization, comparison, and structured response generation. Developed a Streamlit-based interface to interact with the system and display research results in a user-friendly format.
AI-Powered Hotel Review Semantic Search System
January 1, 2026 – Present
Built an AI-powered semantic hotel search engine using review datasets from 15 Pakistani cities. Implemented sentiment analysis using DistilBERT to classify customer reviews. Generated embeddings with Sentence-BERT and indexed them using FAISS for similarity-based retrieval. Developed an interactive Streamlit application for intelligent review search and recommendation. Integrated Google Maps review data for real-world hotel insights.
Automated University Result Scraper
January 1, 2026 – Present
Automated scraping of semester results from the university portal. Parsed roll numbers from Excel and exported structured results back to spreadsheets.
Python for Data science, AI and Development
IBM (Coursera)
June 1, 2026 – Present
100 Days of Code: The Complete Python Pro Bootcamp
Angle Yu (Udemy--)
June 1, 2026 – Present
Machine Learning Specialisation (1/3)
DeepLearning.AI (Coursera)
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong alignment with an AI Engineer role, focusing on diverse applications of AI, machine learning, and deep learning. The breadth of technologies used across projects (Python, Streamlit, Docker, MongoDB, various AI/ML frameworks) indicates adaptability and a willingness to explore different tools. The academic focus suggests a strong theoretical foundation and a passion for learning, which can be a good cultural fit for an innovative environment. However, the lack of professional experience or collaborative projects makes it challenging to fully assess cultural fit in a team setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a strong interest in applying AI to real-world scenarios. The academic nature of all projects suggests a learning-oriented mindset. However, without professional experience or psychometric test results, it's difficult to assess operational fit, teamwork, or stress handling capabilities.