MINSIYA MOL M
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Entry-level AI Engineer with Python, Computer Vision, and Software Testing skills
Computer Science Professional with a B.Tech in Computer Science & Engineering, a minor in Mechatronics, and a CGPA of 8.3. Hands-on experience in Python automation, software testing, neural networks, computer vision, and IoT systems. Skilled in manual testing, functional testing, regression testing, and bug reporting following SDLC and STLC methodologies. Proven ability to design, test, and deploy AI-powered applications. Seeking a software engineering or QA testing role to deliver high-quality software solutions and contribute to impactful products.
Nehru College of Engineering and Research Centre
B.Tech · Computer Science & Engineering
August 1, 2022 – June 30, 2026
KCP HSS Kavassery
Higher Secondary (XII) · Science
June 1, 2020 – May 31, 2022
KCP HSS Kavassery
Secondary School (X)
June 1, 2019 – May 31, 2020
Stem Robotics International Pvt. Ltd
Python Programming Intern
May 1, 2024 – July 1, 2024
Cochin, Kerala, India
AEGISCARE – Multi-Modal AI-Based Elderly Assistance and Monitoring System (Major Project)
June 1, 2026 – Present
Developed an AI-powered elderly assistance and monitoring system to enhance safety, healthcare, and independent living. Implemented real-time fall detection and inactivity monitoring modules for emergency alert generation and rapid response. Integrated a medicine reminder system to help elderly users take medications on time through automated alerts. Designed an object detection module to identify and locate essential daily-use items for improved convenience and accessibility. Utilized AI and IoT technologies to create a user-friendly smart healthcare solution focused on elderly well-being and daily support.
Anomaly Detection Using Neural Network for Smart Surveillance (Mini Project)
June 1, 2026 – Present
Designed and developed an AI-powered surveillance system for automatic anomaly detection in real-time video streams. Implemented a Convolutional Neural Network (CNN) model to identify unusual activities and motion patterns. Utilized TensorFlow and OpenCV for video processing, model training, and live monitoring. Integrated an automated alert notification system to instantly report detected anomalies to operators. Optimized model accuracy through dataset preprocessing and hyperparameter tuning.
Introduction to Machine Learning
NPTEL - IIT Madras
June 1, 2026 – Present
Industrial IoT (IIoT)
NPTEL – IIT Kharagpur
June 1, 2026 – Present
B.Tech - Computer Science & Engineering with Minor in Mechatronics
Nehru College of Engineering and Research Centre
January 1, 2026 – Present
Python Programming
Stem Robotics International Pvt. Ltd
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's projects, AEGISCARE and Anomaly Detection, demonstrate an interest in applying AI to real-world problems with social impact (elderly care, surveillance). The minor in Mechatronics and certifications in Industrial IoT suggest a broad technical curiosity and a willingness to learn across disciplines. The academic projects are diverse in their application areas, indicating adaptability. However, as an entry-level candidate, the breadth of professional experience is limited, which might impact immediate cultural integration into a fast-paced, senior-level environment without mentorship.
Soft Skills & Operational Fit
The candidate's resume highlights teamwork, communication, problem-solving, and debugging as soft skills. Project descriptions indicate collaboration and a focus on user-friendly solutions. The internship experience involved working with a cross-functional team, suggesting an ability to operate in a collaborative environment. However, without specific behavioral assessment data, the depth of these soft skills and operational fit cannot be fully assessed.