AI Engineer with less than a year in AI/ML development, data analysis, and feature engineering.
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Shamitha HP is an aspiring Machine Learning Engineer with 5 months of hands-on experience in developing and optimizing ML pipelines, extracting actionable insights from data, and improving model performance. With a strong foundation in Python, SQL, and various ML libraries, she has contributed to projects involving AI travel assistants, car sales data analysis, and face detection systems, demonstrating strong problem-solving skills and cross-functional collaboration.
Navkis College of Engineering
Bachelor of Engineering · Artificial Intelligence & Data Science
August 1, 2021 – June 30, 2025
Gnanadhare PU College
Class XII · State Board
June 1, 2019 – May 31, 2021
Podar International School
Class X · ICSE
N/A – May 31, 2019
Analogica Software Development Pvt. Ltd.
Machine Learning Intern
October 1, 2024 – February 28, 2025
Bengaluru, Karnataka, India
Exploratory Data Analysis - Car Sales Dataset
June 24, 2026 – Present
Identified sales and demand trends by analyzing seasonal patterns, pricing behavior, and customer preferences across car models. Quantified feature impact on sales performance by evaluating correlations between price, mileage, fuel type, and engine size. Delivered data-driven insights that supported pricing and market strategy decisions through clear visualizations and summaries.
View ProjectFace Detection & Recognition System (OpenCV)
June 24, 2026 – Present
Implemented real-time face detection using Haar Cascade classifiers with OpenCV. Improved execution efficiency by optimizing image processing pipelines using NumPy and OS-level operations. Developed a face recognition module using LBPH, enhancing recognition accuracy in real-time scenarios.
View ProjectTravia - Chat. Plan. Execute. | Al Travel Assistant
June 24, 2026 – Present
Built an AI-powered travel planning application by integrating multiple LLM APIs and NLP techniques to generate contextual itineraries. Improved response accuracy and relevance by designing structured workflows for destination insights and itinerary planning. Optimized system performance by evaluating and selecting LLM models based on response quality, latency, and consistency.
View ProjectCultural Fit Analysis
The candidate's projects show a diverse interest within AI, from LLM applications to computer vision and data analysis, indicating adaptability and a broad learning curve. The internship experience in a software development company suggests an understanding of professional environments. The focus on AI and Data Science aligns well with an AI Engineer role, demonstrating a clear career path and passion for the field. However, the candidate is still early in their career, and their cultural fit would benefit from further assessment during interviews.
Soft Skills & Operational Fit
The candidate demonstrates problem-solving, analytical thinking, and cross-functional collaboration skills through project descriptions and internship experience. The ability to translate technical findings into clear documentation and collaborate with stakeholders indicates good operational fit. However, without specific psychometric test results, a deeper assessment of work attitude, stress handling, and team collaboration is not possible.