Software Engineer – Image Processing & Machine Vision

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Role Overview

Software Engineer

Key Responsibilities

• Design and implement image processing algorithms for camera-based systems.
• Develop, train, and optimize deep learning models for

  semantic segmentation

  and

  object detection

  .
• Apply architectures such as

  Mask R-CNN

  ,

  VGG16

  ,

  SegNet

  , and

  U-Net

  for segmentation tasks.
• Build and deploy

  CNN-based models

  for detecting surface defects in machine vision contexts.
• Perform data preprocessing, augmentation, and annotation for training datasets.
• Integrate trained models into production environments ensuring real-time performance.
• Collaborate with cross-functional teams to define requirements and deliver robust solutions.

Required Skills & Qualifications

• 3–5 years

  of hands-on experience in

  image processing

  and

  computer vision

  .
• Strong proficiency in

  Python

  and libraries such as

  OpenCV

  ,

  TensorFlow

  ,

  PyTorch

  , or

  Keras

  .
• Experience in

  training and inferencing deep learning models

  for segmentation and defect detection.
• Solid understanding of

  CNN architectures

  and their application in machine vision.
• Familiarity with GPU-based training and optimization techniques.
• Knowledge of deployment frameworks (e.g., TensorRT, ONNX) is a plus.

Preferred Qualifications

• Experience in industrial automation or manufacturing environments.
• Exposure to real-time image processing and embedded systems.
• Understanding of quality control processes and defect classification.