AI Engineer with less than a year in Machine Learning & Web Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Currently pursuing a Bachelor of Engineering in Artificial Intelligence and Machine Learning, Agamya L B is a highly motivated entry-level AI Engineer with strong foundational skills in programming (C, Java), web development (HTML, CSS, JavaScript, PHP), and databases (MySQL, MongoDB). She has applied her knowledge in notable projects such as a Cattle Breed Identification system using CNN and an AI/ML-based Sentiment Analyzer. Her certifications in Git, Agile Development, Data Structures, and Algorithms further complement her technical proficiency, preparing her for innovative roles in AI and software engineering.
BMS Institute of Technology and Management, Bengaluru
Bachelor of Engineering · Artificial Intelligence and Machine Learning
August 1, 2023 – June 30, 2027
MES Chaitanya PU College, Sirsi
PU in PCMB · Physics, Chemistry, Mathematics, Biology
June 1, 2021 – May 31, 2023
Cattle Breed Identification using CNN (EfficientNet)
January 1, 2026 – Present
Developed an image-based deep learning system to automatically identify and predict cattle breeds using an EfficientNet-based Convolutional Neural Network. Achieved 92.4% classification accuracy on the validation dataset. Improved model performance by 15% accuracy gain compared to a baseline CNN.
Inventory Management System using XAMPP & MySQL
January 1, 2026 – Present
Designed and developed a web-based inventory management application for item tracking and stock control. Implemented basic CRUD operations and authentication. Enabled efficient stock updates, accurate record management, and reduced manual data handling.
Sentiment Analyzer using AI/ML
January 1, 2026 – Present
Created an AI/ML-based sentiment analysis system to automatically classify user-generated text into positive, negative, or neutral sentiment. Achieved 88.7% overall classification accuracy on test data.
Git & Agile Development
Infosys Springboard
June 1, 2026 – Present
Data Structures & Algorithms
Infosys Springboard
June 1, 2026 – Present
Achieved 85% on an intern-level Java test, indicating a solid grasp of foundational Java programming.
Strengths
Limitations
Scored 79% on a junior engineer level Java test, showing a good but not perfect understanding of more advanced Java and potentially Spring concepts.
Cultural Fit Analysis
The candidate's academic projects demonstrate initiative and a focus on AI/ML, aligning well with an AI Engineer role. The diversity of projects (image classification, sentiment analysis, inventory management) shows a breadth of interest, though the inventory system is less directly relevant to AI. The low psychometric score suggests a potential mismatch in work attitude or collaboration style, which needs to be explored.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on defined tasks and achieve measurable outcomes (e.g., 'Achieved 92.4% classification accuracy'). The academic nature of projects suggests a learning-oriented individual. The psychometric test score is low, which might indicate potential challenges in logical reasoning, work attitude, stress handling, or team collaboration, requiring further investigation during interviews.
Strengths
Limitations