Computer Vision Engineer

N8XT AEROSPACE PTE. LTD.

Singapore

On-site

SGD 60,000 - 90,000

Full time

8 days ago

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Job summary

N8XT Aerospace PTE. LTD.

in Singapore is seeking a computer vision / image processing engineer to develop and implement algorithms and software tools for real-time image analysis from multiple mission-critical sources such as electro-optical and thermal sensors. You will research imaging systems, calibrate cameras outdoors, design and test processing components, and optimize algorithms with parallel computing and ML.

Qualifications

  • Bachelor's degree or higher in computer science, physics, mathematics or a related field.
  • Experience in image processing and/or computer vision, preferably outdoor systems.
  • Hands-on experience in the image processing pipeline (zoom, focus, AWB, color conversion).
  • Knowledge of Kalman filtering, statistical analysis and image processing techniques.
  • Proficiency in Python, C++, MATLAB or other programming languages.
  • familiarity with OpenCV, TensorFlow, PyTorch, scikit-image or PIL.

Responsibilities

  • Research imaging systems and validate them.
  • Calibrate cameras for outdoor real-time mission-critical applications using optical metrology techniques.
  • Design and test image processing systems and components (filters, edge detectors, feature extractors, classifiers).
  • Optimize performance and accuracy of image processing algorithms using parallel computing and ML/DL techniques.
  • Collaborate with data scientists, engineers, researchers and clients to understand requirements.
  • Document and present results and findings of image processing experiments and analyses.

Skills

Python
C++
MATLAB
OpenCV
Machine Learning
Deep Learning
Image Processing
Kalman Filtering
scikit-image
NumPy

Education

Bachelor's degree or higher in CS/Physics/Math

Tools

OpenCV
TensorFlow
PyTorch
scikit-image
PIL
NumPy

Job description

The computer vision / image processing engineer is responsible for developing and implementing algorithms and software tools to process and analyse images for various object detection applications from multiple real-time mission-critical image sources, such as electro-optical, thermal imaging sensors and other sensors.

The job scope includes:
  • Research various imaging systems and validate them.
  • Using optical metrology techniques, calculate and calibrate cameras for outdoor real-time mission-critical applications
  • Designing and testing image processing systems and components, such as filters, edge detectors, feature extractors, classifiers, etc
  • Optimising the performance and accuracy of image processing algorithms using techniques such as parallel computing, machine learning, deep learning, etc
  • Collaborating with other data scientists, engineers, researchers, and clients to understand the requirements and specifications of image-processing projects
  • Document and present the results and findings of image processing experiments and analyses
Requirements:
  • A bachelor's degree or higher in computer science, physics, mathematics or a related field
  • Experience in image processing and/or computer vision, preferably outdoor systems
  • Deep understanding of the imaging systems' sensor characteristics, optical metrology techniques and image signal processing
  • Hands-on experience in the image processing pipeline. (Zoom and focus, auto white balance, camera colour conversion, colour space and colour management, etc.)
  • Expertise in identifying diverse colour issues within intricate ISP systems and in precision tuning of parameters to achieve optimal image quality
  • Knowledge of mathematical modelling, statistical analysis and image processing techniques. (Kalman filtering etc.)
  • Proficiency in Python, C++, MATLAB or other programming languages
  • Familiarity with popular frameworks and libraries for image processing and machine learning, such as OpenCV, TensorFlow, PyTorch, scikit-image or PIL
  • Ability to work independently and as part of a team
  • Excellent communication and problem-solving skills
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