Machine Learning Engineer - Computer Vision

Placements24

Paarl

Hybrid

ZAR 800,000 - 1,100,000

Full time

7 days ago
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Benefits offered by this job

Competitive salary
Performance bonuses
Hybrid work
Health coverage
Career development
Engaging AI projects

Job summary

Placements24 in Paarl is seeking a specialized Machine Learning Engineer with a focus on computer vision to develop and deploy advanced vision models for image recognition, segmentation, and object detection. You will work with large image and video datasets to build systems that perceive and interpret the visual world.

The role offers a hybrid work setup in the Western Cape, a competitive salary with performance bonuses, and strong opportunities for skill development in a growing AI field.

Qualifications

  • Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on computer vision.
  • 3+ years of experience in developing and deploying computer vision models.
  • Proficiency in Python and deep learning frameworks like TensorFlow, PyTorch, or Keras.
  • Experience with image processing libraries (e.g., OpenCV) and data augmentation techniques.
  • Strong understanding of convolutional neural networks (CNNs) and other deep learning architectures for vision tasks.

Responsibilities

  • Design, implement, and train deep learning models for computer vision tasks such as image classification, segmentation, and object detection.
  • Process and manage large datasets of images and videos, ensuring data quality and relevance.
  • Optimize computer vision models for performance, accuracy, and efficiency in production environments.
  • Collaborate with software engineers to integrate computer vision capabilities into existing or new products.
  • Stay current with the latest advancements in computer vision research and techniques.

Skills

Python
CNNs
OpenCV

Education

Master's or PhD in CS/EE with CV focus

Tools

TensorFlow
PyTorch
Keras

Job description

About the Role

Our client is seeking a specialized Machine Learning Engineer with expertise in Computer Vision to join their team in Paarl . This role focuses on developing and deploying cutting-edge computer vision models for a variety of applications, from image recognition to object detection. You will work with large-scale image and video datasets, contributing to the creation of intelligent systems that can perceive and interpret the visual world. This is an exciting opportunity to apply your skills in a growth area of AI, contributing to innovative projects within the picturesque Western Cape region.

Key Responsibilities
  • Design, implement, and train deep learning models for computer vision tasks such as image classification, segmentation, and object detection.
  • Process and manage large datasets of images and videos, ensuring data quality and relevance.
  • Optimize computer vision models for performance, accuracy, and efficiency in production environments.
  • Collaborate with software engineers to integrate computer vision capabilities into existing or new products.
  • Stay current with the latest advancements in computer vision research and techniques.
Requirements
  • Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on computer vision.
  • 3+ years of experience in developing and deploying computer vision models.
  • Proficiency in Python and deep learning frameworks like TensorFlow, PyTorch, or Keras.
  • Experience with image processing libraries (e.g., OpenCV) and data augmentation techniques.
  • Strong understanding of convolutional neural networks (CNNs) and other deep learning architectures for vision tasks.
Benefits
  • Competitive salary and performance-based bonuses.
  • Hybrid work arrangement to balance office and remote work for employees in Paarl .
  • Comprehensive health, dental, and vision insurance.
  • Opportunities for skill development and career advancement in a specialized AI field.
  • Engaging work environment contributing to visual intelligence innovations in the Western Cape .
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