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, Self-Supervised and Unsupervised approaches). Having experience in either Deep Learning, Natural Language Processing, Computer Vision or Reinforcement Learning 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 part to local tech meetups and international tech conferences.
- 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.
- Get access to a competitive salary package and benefits.
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
