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AI Engineer with less than a year in Python and machine learning.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Artificial Intelligence and Machine Learning undergraduate with hands-on experience in Python, machine learning, deep learning and web technologies. Interested in building practical AI-driven solutions and continuously improving technical skills through projects and certifications.
Mar Athanasius College of Engineering
B.Tech · Artificial Intelligence and Machine learning
August 1, 2022 – June 30, 2026
Vimalagiri Public School
Senior Secondary (CBSE)
June 1, 2020 – May 31, 2022
SMART GLOVE FOR SIGN LANGUAGE RECOGNITION
January 1, 2026 – January 1, 2026
Designed and built a wearable smart glove using flex sensors and an Arduino microcontroller to capture hand gesture data in real time.
ENHANCED POST-DISASTER SURVIVOR DETECTION SYSTEM
January 1, 2025 – January 1, 2025
Built an AI pipeline combining YOLOv8 for real-time object detection with BERT-based Transformer models for scene context analysis and false-positive reduction.
IoT workshop
Rever Tech
June 1, 2026 – Present
5 day Internship on building a Foundational AI project
AccelerateX
June 1, 2026 – Present
NPTEL course in Joy of Computing
NPTEL
June 1, 2026 – Present
Prompt engineering workshop
AccelerateX
June 1, 2026 – Present
Robotics workshop
ASME
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects, certifications, and stated interests (Emerging AI tools, Technology trends) align well with an AI Engineer role, demonstrating a passion for the field. The diversity of projects (wearable tech, disaster response AI) shows a breadth of application interest. However, the lack of professional experience means cultural fit in a corporate environment is largely unproven.
Soft Skills & Operational Fit
The candidate's resume indicates an interest in practical AI-driven solutions and continuous skill improvement, suggesting a proactive and learning-oriented attitude. Project descriptions are concise, indicating a focus on technical outcomes. However, without direct work experience or detailed project methodologies, it's difficult to assess collaboration, problem-solving under pressure, or communication in a team setting.