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Embedded Systems Engineer with less than a year in Machine Learning & IoT.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
To utilize my Electrical Engineering skills, with a major in Computer Engineering, in the field of Embedded systems and to improve my theoretical knowledge by implementing it in real-world problems. Machine learning Expertise lie in colab programming, Tensorflow, pytorch, scikit learning C/C++ programming, Hardware/Software integration and PCB designing
COMSATS University Islamabad
Bachelor's · Electrical Engineering
January 1, 2020 – January 1, 2024
Government Degree College Karor
Secondary School Certificate · Pre-Engineering
N/A – Present
Government Railroad School Karor Lal Easan
Secondary School Certificate
N/A – Present
elevvo.tech
Machine Learning Track
July 1, 2025 – August 1, 2025
Cairo, Cairo Governorate, Egypt
Veevo tech
Embedded system design
April 1, 2025 – May 1, 2025
National Institute of Electronics
Embedded Systems Intern
August 1, 2023 – September 1, 2023
Islamabad, Islamabad Capital Territory, Pakistan
Smart energy meter with IoT
June 10, 2026 – Present
Goal: IoT meter using ESP32 to measure V, I, kWh and send to app. Hardware: ESP32, ZMPT101B, ACS712, LCD, Relay. Working: Reads power, uploads to Firebase, relay cuts load remotely. Use: Real-time billing, tamper alert, costs Rs. 4k.
FINAL YEAR PROJECT
June 1, 2023 – July 1, 2024
Gunfire distress and anomalies detection using audio signature by deep learning Machine Learning Integration of MobileNet V2 model with 98% accuracy. Implementation using Raspberry Pi 8. • Designed and implemented Machine learning project
certification of elevvo.tech
elevvo.tech
August 27, 2025 – Present
Certification of WordPress Course
Unknown
December 1, 2020 – Present
Cultural Fit Analysis
The candidate's projects and internships show a strong interest in both embedded systems and machine learning, which aligns well with innovative and technically diverse environments. The academic background in Electrical Engineering with a major in Computer Engineering provides a solid interdisciplinary foundation. The diversity of projects (IoT, ML on edge, PID control) suggests adaptability and a willingness to explore different technical domains. However, the lack of team-based project descriptions makes it difficult to assess collaboration and cultural integration fully.
Soft Skills & Operational Fit
The candidate demonstrates a proactive learning attitude through self-initiated projects and internships. The project descriptions indicate an ability to work on practical problems and integrate different technologies. However, the descriptions lack detail on problem-solving approaches, challenges faced, and specific contributions, which limits the assessment of operational fit and collaboration skills.