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I will build and deploy custom ai models for edge devices
Danh Huynh Minh
About this gig
I will train, optimize, and deploy custom AI models
on any edge device. Specializing in computer vision,
real-time inference, and model optimization using
TensorRT, ONNX, and quantization techniques for
embedded systems like Jetson, Hailo, Raspberry Pi,
and more.
Get to know Danh Huynh Minh
Danh Huynh Minh
- FromVietnam
- Member sinceJun 2021
- Avg. response time1 hour
Languages
English
AI & Embedded Engineer specializing in edge AI
deployment and model optimization for 2+ years.
I deploy real-time AI on NVIDIA Jetson, Hailo-8,
and Raspberry Pi using TensorRT, ONNX, and INT8
quantization — achieving 60+ FPS with 90%+ accuracy.
What I deliver:
- AI model training & fine-tuning
- Edge optimization (TensorRT, quantization, CUDA)
- Computer vision: detection, classification, anomaly detection
- Clean, production-ready C++/Python code
Previously deployed YOLOv11 at 60 FPS on
Raspberry Pi 5 + Hailo-8 for real-time inference.
Let's bring AI to your edge device. Message me!
FAQ
What information do you need to get started?
Please provide: (1) your AI task type (object detection, classification, etc.), (2) your edge device model, (3) your dataset or pre-trained model if available, and (4) your performance requirements (FPS, accuracy, latency).
what edge devices do you support?
I support a wide range of edge devices including NVIDIA Jetson , Hailo-8, Raspberry Pi, and other embedded Linux systems.
Do you provide the source code?
yes, all packages include full source code with detailed comments so you can maintain and modify it yourself.
What if I don't have a dataset?
I can help you collect, prepare, and annotate a custom dataset, or use publicly available datasets that match your use case. This may affect delivery time.
Can you guarantee real-time performance?
Performance depends on your device hardware and model complexity. I will always benchmark and optimize to achieve the best possible FPS and latency for your specific hardware.
