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Applied Machine Learning Enginee...

412labs.com
Cairo, Egypt

Applied Machine Learning Engineer / Computer Vision Scientist

Cairo, EgyptPosted 2 months ago
90Applicants for1 open position
  • 4Viewed
  • 0In Consideration
  • 0Not Selected

Job Details

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Job Description

The main focus is to develop turn-key hardware and software solutions using applied machine
learning and computer vision deployed at the edge. As an Applied Machine Learning Engineer,
you will work with our research team and industry collaborators to develop custom solutions. You
are responsible for wrangling and preprocessing terabytes of data, system pipeline design and
training, and model runtime performance.
You will be in charge of implementing and testing algorithms for various machine learning tasks.
Most of the tasks will involve working on typical computer vision problems, such as object
detection, keypoint detection, object recognition, object segmentation, activity/action detection,
image pre-processing, blur estimation, etc. You will utilize existing hardware and images in
addition to new image data gathering techniques to produce innovative image analysis models
and algorithms. You will develop ML approaches that improve the speed and accuracy of image
algorithm development for oilfield applications.


● You are highly motivated, have a positive attitude, have a passion for creating and
supporting great products and a results oriented approach to work
● You thrive on collaboration, working side by side with people of all backgrounds and
disciplines, and you have very strong verbal and written communication skills. You speak
English fluently.
● You are great at solving problems, debugging, troubleshooting, designing and
implementing solutions to complex technical issues.
● Scientific understanding of popular/state-of-the-art deep learning architectures and
computer vision algorithms for object detection and object segmentation.
● Ability to read scientific publications, understand and implement proposed solutions.

Successful candidates will:

● Lead the ideation, prototyping, and development of AI software.
● Demonstrate expertise in solving computer vision problems.
● Develop deep learning and traditional machine learning algorithms.
● Design and develop scalable software architectures.
● Facilitate design and deployment of vision hardware equipment needed for image data
gathering. Support testing during the validation process.
● Facilitate and lead data gathering, collaboration with annotation teams, data quality
validation and production data monitoring.
● Create and maintain data pipeline architecture for ML algorithm development.

Job Requirements

  • PhD or MSc in Computer Science, Engineering, Mathematics or Statistics, with
    specialization in computer vision and deep learning
  • Minimum of 2 years (candidates with PhD) and minimum of 4 years (candidates with
    Masters) of industrial experience in developing Computer Vision and Deep Learning
    applications in Python/C++.
  • Experience in multi-facility, international organizations desired.
  • Successful delivery of machine learning applications to internal or external customers.
  • Proficiency in Deep Learning frameworks (Tensorflow, Keras or Pytorch)
  • Proficiency in Python, C++ appreciated
  • Proficiency in CV/ML libraries (OpenCV, Scikit-learn, Numpy, Pandas)
  • Proficiency in implementing deep learning architectures for Image classification, Object
    detection, Object segmentation and Action/Activity detection.
  • Demonstrated experience in scientific research related to Computer vision and Deep
    learning.
  • Scientific thinking and the ability to invent, implement, and lead technology developments
    in the field of computer vision and machine learning.
  • Demonstrated experience deploying models on Edge devices like Raspberry Pi, Nvidia
    Jetson, or similar.
  • Demonstrated experience extracting / applying software from open source repos
  • Excellent problem solving skills in the face of ambiguity using a clear understanding of
    facts and implementation of test plans and solution strategies

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