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AI Engineer with 2+ years in Machine Learning & Data Analytics
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Highly skilled Machine Learning Engineer and Executive in AI Analytics with 2.7 years of experience in developing and deploying AI solutions. Proven expertise in building backend services for AI agents, managing LLM-based conversational workflows, optimizing object detection and spatial analysis, and driving data-driven decision-making. Strong background in Python, AWS, Docker, and various ML/DL frameworks, coupled with a Master’s degree in Data Science and a passion for leading innovative AI projects.
University of Engineering & Technology, Lahore
MSc. · Data Science (Weekend)
August 1, 2024 – June 30, 2025
University of Engineering & Technology, Lahore
Bachelors of Science · Electrical Engineering (Computer Major)
August 1, 2019 – June 30, 2023
Kavtech Solutions (Private) Ltd.
Machine Learning Engineer
October 1, 2025 – Present
Lahore, Punjab, Pakistan
AERODYNE GROUP
Executive - AI Analytics
March 1, 2024 – October 1, 2025
Lahore, Punjab, Pakistan
University of Engineering & Technology, Lahore
Graduate Teaching Assistant
October 1, 2023 – March 1, 2024
Lahore, Punjab, Pakistan
Research Trend Forecasting in Computer Science using LDA (Latent Dirichlet Allocation) and LSTM
January 1, 2025 – December 31, 2025
Built an end-to-end forecasting pipeline using 20 years of Scopus data from 20 Computer Science journals. Applied LDA to model 200 yearly topic distributions; clustered and matched them to 25 high-level research themes using TF-IDF, KMeans, and sentence transformer (all-MiniLM-L6-v2). Developed an LSTM model with a 10-year sliding window to forecast 3-year future growth in paper volume and citations per topic. Achieved over 85% forecasting accuracy for most topics, revealing top-emerging and stable research domains.
Analyzing Depression Levels using ML/DL on Social Media Data
January 1, 2024 – December 31, 2024
Developed a classification model to detect depression levels using a dataset of 7,731 tweets. Applied preprocessing techniques such as tokenization, lemmatization, and hashtag removal. Trained and compared multiple ML/DL models including Logistic Regression, Naïve Bayes, SVC, Random Forest, RNN, LSTM, and BERT-based hybrid models.
Final Year Design Project: Dengue Surveillance Toolkit
January 1, 2022 – December 31, 2023
Developed a Visual Analytic Syndromic Surveillance Toolkit for Dengue disease analysis. Implemented ML models for forecasting trends, detecting point anomalies, and aggregating data. Applied spatial modeling techniques to generate hotspots based on geographic data.
Time Series Forecasting using AI/ML
January 1, 2022 – December 31, 2022
Developed time series forecasting models to predict trends in different scenarios. Implemented anomaly detection methods to identify unusual patterns in the data.
Building Language Models on AWS
Amazon Web Services (AWS)
June 1, 2026 – Present
Foundations of Prompt Engineering
AWS
June 1, 2026 – Present
Teaching Assistant Certifications for Programming Fundamentals and Introduction to Computing and Data Science
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects show a diverse interest in applying AI/ML to various domains, from research trend forecasting to public health and social media analysis. Their professional roles involve both core ML engineering and AI analytics, indicating adaptability. The certifications in AWS and prompt engineering align well with modern AI development practices. The blend of academic rigor and practical industry experience suggests a candidate who is both intellectually curious and results-driven, fitting well into a dynamic technical culture.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations (e.g., research trend forecasting, dengue surveillance). Their experience as a Graduate Teaching Assistant suggests good communication and mentoring abilities. The role at AERODYNE GROUP highlights attention to detail, process optimization, and collaboration in a production environment. The ability to maintain documentation and contribute to product testing indicates a structured and quality-oriented approach.