The scikit-learn is a Python module for machine learning. The project builds on the scientific and numerical tools of the scipy community to provide state-of-the-art data analysis tools. It is developed by a community of open source developers to which my research team (Parietal, INRIA) contributes a lot and is a striving project. Its mailing list fosters many discussions on code and machine learning topics, it has a a very detailed documentation, and a tight release cycle.
Although scikits.learn is mostly developed by volunteers, INRIA has funded a two year position for a junior engineer —currently Fabian Pedregosa— to help with the core management and integration of the project. This funding is coming to an end in falls 2011 [*]. The good news is that we have been allocate new funding to hire an engineer on the scikit.
We are thus looking to hire a junior engineer for a 2-year position to work on the scikits.learn at INRIA in Saclay, near Paris. The position is only available to candidates that have received a masters or equivalent degree at most a year ago — this is non negotiable: we cannot hire more senior candidates.
We are looking for a developer with good open-source project management skills: the successful candidate will review and merge patches, ensure the quality of the scikit, make releases, coordinate development on the mailing list and on github. Good knowledge of Python and its scientific ecosystem is expected. A mathematical or computer-science oriented mindset is a plus, as the project involves working with machine learning algorithms.
The candidate should be willing to relocate to work daily in the Neurospin brain research institute in which the Parietal is located. Knowledge of French is not required, as the team and the institute are very international. Non-EU candidates are welcome, but the hiring process will take longer.
You will be working in a very stimulating environment. You will be employed by INRIA, the French computer science research institute. As such, you will benefit from the expertise of the institute’s researchers and engineers. Team members contribute to various scientific Python libraries (in addition to scikits.learn, Mayavi, nipy, joblib). In addition, you will be working in a brain research institute, in collaboration with leading methods researchers and neuroscientists that use machine learning to gain new insights on brain processes.
To apply: To apply, you need to prepare a CV and a motivation letter. The deadline for applications is mid June, but we will be selecting candidates and conducting interviews before. Don’t send me CVs. The formal job description, as well as instructions to apply can be found on this page. The page is mostly in French, sorry; use Google translate if you don’t understand. At the bottom of the page you will find a link to apply.
[*] Fabian will most probably stay with us to do a PhD on analysis of large brain functional imaging datasets.
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