ABDULSAMATH G
@abdulsamathg
I build embedded AI systems for real-time automotive and industrial edge applications.
What I'm looking for
At EinNel Technologies, I develop embedded AI software for driver monitoring systems on Qualcomm QCS6490 hardware, achieving 25 FPS real-time inference for eye-blink detection, gaze estimation, yawning detection, and driver distraction analysis.
I integrate ONNX deep learning models with Qualcomm NPUs and embedded Linux platforms, validating latency, model performance, camera hardware, and deployment readiness on edge devices.
I also build C/C++ and Python software for sensor streaming, hardware bring-up, embedded peripherals, backend APIs, and industrial communications using OPC UA, MQTT, and Modbus TCP.
My work spans predictive maintenance pipelines, Digital Twin platforms, synthetic data generation, and computer-vision deployment for automotive and industrial IoT applications.
Experience
Work history, roles, and key accomplishments
Associate Embedded Engineer
EinNel Technologies
Jul 2023 - Present (3 years 1 month)
Developed embedded software for a Driver Monitoring System achieving 25 FPS real-time inference on Qualcomm QCS6490 using ONNX Runtime. Integrated ONNX models on embedded hardware, performed model validation, and worked on hardware bring-up and industrial communication protocols.
Education
Degrees, certifications, and relevant coursework
Vels Institute of Science Technology and Advanced Studies
Bachelor of Engineering, Electronics and Communication Engineering
2019 - 2023
Grade: 8.73/10
Bachelor of Engineering in Electronics and Communication Engineering with a CGPA of 8.73/10.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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