AI Engineer with less than a year in Machine Learning & Chatbot Development
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AI/ML Engineer Intern with 5 months of hands-on experience in building and optimizing ML models for classification, prediction, and chatbot development. Proven ability to process and analyze real-world datasets, apply feature engineering, and design AI solutions. Skilled in prompt engineering for content generation pipelines and committed to enhancing model accuracy and efficiency.
FAST National University of Computer and Emerging Sciences
Bachelor of Science · Artificial Intelligence
August 1, 2022 – June 30, 2026
Kneva
AI/ ML Engineer Intern
February 1, 2026 – March 31, 2026
India
ViewsPanda
Machine Learning Intern
June 1, 2025 – August 31, 2025
India
Cross Domain Anomaly Detection
June 24, 2026 – Present
Implemented and optimized a GeneralAD model for cross-domain anomaly detection using self-attention and FP16.
Product Recommendation Site with Chatbot
June 24, 2026 – Present
Built a web app that scrapes product data and delivers chatbot-based recommendations with interactive visualizations.
AI-Driven Real Estate Recommendation Renovation
June 24, 2026 – Present
Developed an AI-powered platform for predictive property recommendations and generative renovation insights. Enabling users to identify, evaluate, and optimize real estate investments using data-driven analysis.
Neural Networks Deep Learning
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including AI-driven real estate, product recommendations, and anomaly detection, shows a broad interest in applying AI across different domains. Their involvement in university activities and international collaborations suggests an open, engaged, and team-oriented personality. The target role of AI Engineer aligns well with their academic background and practical experiences, indicating a strong potential for cultural fit within an innovative AI-focused environment.
Soft Skills & Operational Fit
The candidate demonstrates a collaborative spirit through team project involvement and contributions to university operations. Their internship experiences suggest an ability to work within industry-standard workflows and focus on performance optimization. The project descriptions indicate a problem-solving mindset and an interest in applying AI to real-world scenarios.