I will deploy your ml models

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deploy your ml models
deploy your ml models
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deploy your ml modelsdeploy your ml models

Über diesen Service

Get your ML model running fast on edge hardware.


I convert PyTorch or TensorFlow models to ONNX, then optimise for NVIDIA Jetson (TensorRT), Intel edge (OpenVINO), or Raspberry Pi. Typical result: 3x to 10x faster inference on the same device.


What you get:


- Optimised model file (TensorRT engine, OpenVINO IR, or ONNX)

- Benchmark on your target hardware (FPS, latency, memory)

- Accuracy comparison against your original model

- Written notes explaining the trade-offs I made


I have 7+ years of production computer vision experience, deployed at industrial customers across Europe. I am currently CTO of an industrial AI startup.


Send me: your model file (or a Colab notebook), target hardware, and target FPS. I will confirm feasibility before you order.


Hardware I regularly work with:

- NVIDIA Jetson Nano, Xavier NX, Orin Nano, Orin AGX

- Raspberry Pi 4 and 5 (with or without Coral USB accelerator)

- Intel NUC, Intel edge devices via OpenVINO


Models I have optimised: YOLO family (v5, v7, v8), Mask R-CNN, U-Net, EfficientNet, MobileNet, custom CNNs.

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Lerne Mutte U kennen

Mutte U

CTO Edge AI Engineer I deploy computer vision on Hardware

  • AusFrankreich
  • Mitglied seitAug. 2025

  • Sprachen

    Englisch, Französisch
Edge AI, computer vision, and embedded systems, from prototype to production. I ship real-time CV on portable camera hardware for industrial customers. Fluent in C++, Python, PyTorch, TensorFlow, ONNX, TensorRT, OpenVINO, Jetson, Raspberry Pi, ESP32, Arduino, PCB design. I move fast, I document what I ship, and I explain the choices so you learn from the engagement. MSc Computer Vision and Robotics (VIBOT). Paris, France.

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