Machine Learning Enthusiast

About us:
Our company is governed by “your freedom is gold, Why work in a framework of the 90s with the tools of today?”. We have Kaggle type problems of the real-world and your performance is rewarded in a monetary value instead of a podium of competitors, by the way Kaggle and GitHub are good tools to define your competences !

Our collaborative work is based on:

  • Big Data
  • Cloud computing
  • Data encrypted in the cloud
  • Open source software
  • Remote work
  • BYOD (if needed)

For this [position/problem test] your team will be:

  • A PhD expert in Machine Learning
  • A PhD in Operational System and Optimization
  • A PhD in Statistics
  • A professional in Statistics (finishing master’s degree)
  • A professional in Statistics
  • Several operational experts in the problem domain
  • Another trainee in artificial intelligence

The candidate will have very interesting challenges in a context of Big Data and artificial intelligence with tasks of the type (estimated percentage of your time):

  • Set up routines for cloud computing on AWS, Azure, Google Cloud, etc. (10%)
  • Evaluate parametric models of learning, e.g. a mixture of Gaussians (10%)
  • Test different models of Machine Learning (60%):
    – Clustering
    – Decision trees
    – Support Vector Machine (SVM)
    – Hidden Markov Models (HMM)
  • Evaluate the statistical performance of models, p. ex. T-type test, F test, McNemar’s Test, etc (20%).

It will be considered an asset the following skills:

  • Produce auto-executable for Linux/Unix/Windows