DevOps and Big Data Integrator

🦾 BACKGROUND AND MISSION

We are looking for an Intern to work on the Prototyping and implementation of a platform and join our Space business unit in the Skill Center DevSecOps. The DevSecOps Skill Center is at the heart of our solutions for the valorisation of spatial data:

  • DevSecOps " INFRA" : Prototyping, optimization and scaling of reliable & interoperable Cloud/HPC infrastructures,
  • DevSecOps " User eXperience & SERvices " : Development of high value-added applications based on spatial data (and more).

🎯 Your mission 

You will participate in the prototyping, testing and deployment of an AI-driven geospatial platform in the cloud.

Using the DevOps philosophy, you will :

  • deploying AI frameworks such as Tensorflow, Keras and Seldom,
  • to integrate them in a Jupyter environment, to validate them,
  • to test/use them,
  • to validate their scalability in the Cloud (sovereign Kubernetes),
  • and to use deployment technologies such as Helm, Kustomize and ArgoCD.

The internship is between the implementation of Cloud platform, and the use of data science tools.

⭐Les Plus of the course:

  • Participate in major issues related to spatial data processing,
  • Get trained in DevOps, Data and AI technologies,
  • Meet technical challenges.

💼 PROFILE

Who are you?

You are looking for a 6 months internship. You like technology and want to work in a team on AI & DevSecOps projects.

We are looking for a
curious, motivated, enthusiastic person
More specifically, knowledge or notions in the following fields would be appreciated

  • Python
  • AI framework (Tensoflow, Keras, ...)
  • DevOps environment (Docker, Helm, Ansible, ...)

So you'll be at the intersection of infrastructure and science, and you have an appetite for this type of platform and AI.

With equal qualifications, this position is open to people with disabilities.


🛰️ Who are we?

CS GROUP contributes to the AI4GEO project, in partnership with CNES, Geosat, ONERA, IGN, QuantCube, CLS and Airbus. This is an ambitious national R&D program that aims at lifting technological barriers for the automatic production of 2D & 3D geographic information, thanks to artificial intelligence methods and Big Data technologies.
Our team brings its expertise in the implementation of Big Data, Cloud and HPC solutions to provide partners with a powerful R&D platform that will eventually produce geospatial information on a global scale from massive satellite, Lidar and Radar data from air and ground platforms.

💻 And of course: the possibility of telecommuting, a co-optation program, complementary health care, RTT, the CE.

🚀Plus:
Participate in an ambitious national research project with major national players in the geographic and spatial fields.
Get trained in the most fashionable technologies in Big Data and AI
Take on technical challenges

What happens next:

If your profile matches, you will have a technical interview with one of our operational managers. Then, you will meet with Eleonore or Elodie for an HR interview. And we promise to get back to you by phone 🙂

#CSGROUP #hiring #Devops #IA #Internship

Send us your CV

Allowed file type(s): .pdf, .doc, .docx

Join the jobs of tomorrow in artificial intelligence and geospatial data

The AI4GEO project aims at developing a set of technological bricks allowing the automated production of 2D and 3D geospatial information based on artificial intelligence techniques, in particular deep learning.

Within this consortium, a common base of deep learning tools for remote sensing is developed, in particular to allow the production of land use maps or the reconstruction of buildings. The engineer in artificial intelligence will be part of the core team of the project and will contribute to the development of this toolbox.

It is also conducting, in conjunction with the Institute's research teams, studies to enable more significant contributions from the Institute; the first of these will thus concern the construction of reference land use data sets for the constitution of pre-trained models with good geographic generalization capabilities and transfer to more specialized tasks.