What you’re going to do

  • Assess, analyse and propose optimal approach to solve specific problems, by leveraging different algorithms and machine learning solutions
  • Work with a broad range of machine learning techniques, from supervised (SMV, Neural Networks, Naive Bayes, Decision Trees, etc.) to unsupervised learning (Clustering, Topic Modeling, etc.)
  • Adapt standard machine learning methods to best exploit modern parallel environments
  • Apply computational algorithms and statistical methods to unstructured data
  • Code deliverables in sync with the development team
  • Combine analytic methods with advanced data visualizations
  • Write clean, well­ engineered, maintainable code that conforms with accepted standards
  • Develop quality code through unit and functional testing
  • Participate in the iteration planning and team standup meetings

What we’re looking for


We think it’s essential to have a continuous drive for self improvement and self motivation. Instead of opposing change, we count on you reshaping your mindset to accommodate the new in your daily craft. Your initiative and accountability will open doors much faster and we trust you’ll do your best in being productive and efficient.

Your positive and team­ oriented attitude will support you in working well with your colleagues. Good communication skills will help you create stronger connections. The secret ingredient to succeed in a rapidly expanding environment is to be highly organized and able to balance multiple simultaneous projects. Whatever the (technical) problem, utilize your skills to be part of the solution.

The difference between something good and something great will be your extreme attention to detail and the consistency of your work. Performing independently, with little supervision, will unlock more of your creativity to encourage you to reach your potential. Your passion towards Machine Learning will fuel your inspiration to come up with original ideas on how to get things done. All these will make a major impact on your results.


To complete the ideal candidate profile, you need to have:

  • BS/MS in Computer Science (advantage if you are working on a PhD degree or contributed to an open source project).
  • Experience with two or more of the following languages: Scala, Java, Python, Ruby
  • Knowledge in machine learning: data mining, Natural Language Processing, learning from unstructured & semistructured data and computer vision
  • Experience with natural language processing toolkits: Wordnet, Stanford NLP, Open NLP, Mallet, Mahout, NLTK, etc.
  • Experience with computer vision techniques: object detection and recognition
  • Knowledge about Neural Networks concepts, more specifically Deep Learning
  • Experience with machine learning frameworks (preferably Tensorflow)
  • Interest in machine-learning applications and willingness to be very hands on to develop new applications and algorithms.
  • Experience with Agile methodologies
  • Good English skills (written and spoken)