ML/CV engineer to $3500

MilTech 🪖

ML/CV engineer

We’re looking for a passionate Machine Learning / Computer Vision Engineer to join our team.

As a member of our team, you will participate in research & development of solutions in the field of computer vision, document understanding using cutting-edge machine learning approaches. The position will involve different aspects of R&D including initial research, analysis, prototyping and development. By joining our team you’ll be able to affect Ukrainian Deftech area innovations and contribute to important today’s military products.

Responsibilities:

  • Research and development of Image Processing algorithms including CV algorithms
  • Research and prototyping of detection and tracking algorithms using ML and CV
  • Work with data collection and analysis in order to improve efficiency of ML/CV dependent algorithms

Job Qualification:

  • 2 years of commercial experience with Python
  • Demonstrated hands-on experience with TensorFlow, PyTorch
  • Practical Experience with Machine Learning, including designing, training, fine-tuning of ML models, and integrating machine learning systems into production environments related to Computer Vision, Document Understanding
  • Experience with Object Tracking area using ML/CV
  • Experience with vision transformer, vision encoder-decoder architectures
  • Strong analytical and communication skills

Will be a plus:

  • Experience in Miltech development
  • Experience with code performance optimization
  • Master’s or Bachelor’s degree in computer science, math, statistics, or related field
  • Experience in C/C++ 

 

 

Working Conditions:

  • official employment 
  • offline work for growing deftech company (remote is also option but mostly offline)
  • military exemption

Required skills experience

Machine Learning 2 years
Computer Vision 2 years
OpenCV 2 years
PyTorch 2 years
Tensorflow 2 years

Required domain experience

MilTech 2 years

Required languages

English B2 - Upper Intermediate
Python, C/C++, Git, MilTech
Published 3 February
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