
AI Engineer with less than a year in Python & AI/ML 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
MCA graduate with a strong foundation in Python, SQL, Data Structures & Algorithms, Networking, and problem-solving. Hands-on internship experience in AI/ML, API integration, and application development. Skilled in testing, debugging, and data analysis with exposure to Agile methodologies. Passionate about building scalable technology solutions.
Visvesvaraya Technological University
Master of Computer Application (MCA)
N/A – June 30, 2026
suprmentr technologies pvt ltd
(online)
January 1, 2026 – May 1, 2026
Bengaluru, Karnataka, India
Email Automation System
June 28, 2026 – Present
Developed a Python-based email notification system using SMTP to automate message receiving in desktop.
AI Meeting Summarizer
June 28, 2026 – Present
Built a Python application to convert speech to text and generate concise meeting summaries.
Library Management System
June 28, 2026 – Present
Developed a database-driven application using PHP and MySQL for managing records.
Alzheimer's Disease Prediction System using CNN
June 28, 2026 – Present
Developed a machine learning model in Python to predict the likelihood of Alzheimer's disease using patient health data.
Machine Learning with Python
IBM
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects are primarily academic, focusing on AI/ML applications. The internship experience aligns with the target role of an AI Engineer. The breadth of skills includes Python, SQL, various ML libraries, and exposure to Agile methodologies, indicating a foundational understanding relevant to modern development environments. However, the experience level is 0, and all projects are academic, which might limit immediate cultural integration into a fast-paced, senior-level industry setting without further mentorship.
Soft Skills & Operational Fit
The candidate lists problem-solving, communication, teamwork, adaptability, time management, quick learning, and analytical thinking as soft skills. These are generally positive for operational fit. However, without specific examples or interview data, the depth of these skills cannot be fully assessed. The academic projects and internship suggest some level of problem-solving and application development.