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