Jabez John
@jabezjohn
Aspiring software engineer specialized in machine learning and IoT.
What I'm looking for
I am an aspiring software engineer with hands-on experience in machine learning, Python, and IoT projects, and I graduated with a BE in Electronics and Communication Engineering in 2025. I have built end-to-end ML workflows, developed a narrative-to-game level generator, and created an AI-powered patient monitoring system using Raspberry Pi.
During internships I worked on data preprocessing, model training and tuning with Scikit-learn and TensorFlow, and contributed to web application development using HTML, CSS, JavaScript, Python frameworks and REST APIs. I am comfortable with collaborative version control using Git and have practical experience applying NLP and procedural content techniques.
I am a quick learner, team player with effective communication skills and strong time management, seeking opportunities to contribute to dynamic teams, build scalable applications, and solve real-world challenges using ML, embedded systems, and software development.
Experience
Work history, roles, and key accomplishments
Machine Learning Intern
Vcodez
Jun 2025 - Aug 2025 (2 months)
Implemented end-to-end ML workflows including data preprocessing, model training, and performance tuning; designed an NLP-driven system to convert narrative text into playable game levels.
Education
Degrees, certifications, and relevant coursework
SRM TRP Engineering College
Bachelor of Engineering, Electronics and Communication Engineering
Grade: 8.21 CGPA
Completed Bachelor of Engineering in Electronics and Communication Engineering with a CGPA of 8.21 in 2025.
Maxwell Matriculation Higher Secondary School
H.S.C., Higher Secondary Certificate
Grade: 80.5%
Completed Higher Secondary Certificate (State Board of Tamil Nadu) in 2020 with a percentage of 80.5%.
Maxwell Matriculation Higher Secondary School
S.S.L.C., Secondary School Certificate
Grade: 76.6%
Completed Secondary School Leaving Certificate (State Board of Tamil Nadu) in 2019 with a percentage of 76.6%.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
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