
AI Engineer with less than a year in Python & Deep Learning
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software Engineering student at Capital University of Science & Technology (CUST) with hands-on experience in Artificial Intelligence, Machine Learning, and Generative AI through internships and formal training programs. Skilled in Python, NLP, and ML model development. Actively participating in hackathons and continuously expanding knowledge through industry certifications.
Capital University of Science & Technology (CUST)
BS Software Engineering · Software Engineering
August 1, 2022 – Present
Punjab Group of Colleges, Blue Area Campus
Intermediate · Computer Science (ICS – Physics)
June 1, 2020 – May 31, 2022
AKSA-SDS
AI & Machine Learning Intern
July 1, 2025 – September 30, 2025
Islamabad, Islamabad Capital Territory, Pakistan
Machine Learning Models Implementation
June 1, 2026 – Present
Implemented and compared multiple ML algorithms including Regression, KNN, Decision Trees, and K-Means clustering.
Sentiment Analysis System
June 1, 2026 – Present
Developed an NLP pipeline to classify user reviews by sentiment using supervised learning techniques.
Text Classification & Topic Modeling
June 1, 2026 – Present
Applied NLP methods to categorize text data and extract latent topics using unsupervised models.
AI for Beginners
HP LIFE
June 1, 2026 – June 1, 2026
Certified in Gen AI
Arfa Karim Tech Incubator (AKTI), Cohort C5
July 1, 2025 – September 30, 2025
Generative AI Training
Pak Angels
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects and certifications show a strong interest in AI and ML, aligning well with an AI Engineer role. The diversity of projects (sentiment analysis, text classification, ML model implementation) and continuous learning through certifications suggest a growth mindset. However, the experience is primarily academic and internship-based, indicating a need for further development in a professional team setting.
Soft Skills & Operational Fit
The candidate's profile suggests a proactive and enthusiastic learner, evidenced by participation in hackathons and continuous certification pursuits. The internship experience indicates an ability to work in a structured environment and apply learned concepts. However, the limited professional experience means operational fit beyond basic task execution is yet to be fully demonstrated.