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Machine Learning Developer

Brussels, Belgium

Our growing team of ML Engineers is looking for new colleagues! If you are a good mix between a machine learning expert, a software developer and you don't shy away from reading scientific papers to learn about new ML approaches, keep reading. At Sagacify, we develop the cutting-edge intelligent software solutions that are revolutionising society thanks to AI.

Required qualifications

  • You are highly self-driven, responsible and keen to learn
  • You are fluent in Python and have experience with one or more of these technologies / libraries:
    • TensorFlow / Keras
    • Pandas
    • Numpy / Scipy
    • Scikit-Learn
    • Open Gym AI
    • Matplotlib
    • Jupyter Notebooks
    • ...
  • You have relevant experience in Machine Learning (Supervised and Unsupervised models). Having experience in either Deep Learning, Natural Language Processing or Computer Vision is a plus.
  • You are familiar with or interested about the current research papers in the field.
  • You have general software engineering skills (i.e. version control system like git, debugging, testing, ...)
  • You are familiar with (big) data handling and processing.
  • You know how to interact with APIs and the external world.
  • Experience with either AWS or Google Cloud Platform is a plus.

Why you will love working with us

  • Be part of a passionate team of technology addicts.
  • Learn and develop your skills in different fields and technologies.
  • Take charge and responsibility for your projects from day one.
  • Collaborate with the whole Sagacify team in a global way, bringing good ideas count more than hierarchies.
  • Work in an environment adapted to your needs with flexible hours. Remote work is also a part of our culture.

For more information, check this video to learn more about our working culture.

Interested ?

Send us the following on hiring@sagacify.com

  • Your CV and cover letter (online CV and LinkedIn profile are welcome)
  • Examples of your work (e.g. GitHub, PDFs, Slideshare, etc.)
  • Tell us a little more about yourself: Blog, Twitter, Tumblr, Flickr or your website, show us your extracurricular interests