Software Engineer within the Moose Team, focused on P16

The EVREF project team is dedicated to the continuous evolution of large software systems, offering innovative solutions for their maintenance, evolution, and reengineering. At the heart of this work is MOOSE, an advanced software platform dedicated to the analysis of complex software systems. It is built on a meta-model layer and has strong academic and industrial recognition.

The P16 project, supported by France 2030, aims to accelerate the industrialization of AI software components while promoting their dissemination. It focuses on data interoperability, automation of data processing, and the training and execution of AI models.

The proposed position aims to strengthen synergies between Moose and P16 by integrating the specific requirements related to the evaluation of software libraries developed within P16, while leveraging Moose’s advanced capabilities and extending them to effectively support the work of data scientists.

• Development and Integration for P16:
  • Develop software quality rules tailored to the software integrated into P16.
  • Design a rule engine to evaluate software libraries.
  • Explore the definition of a quality model for the data scientist profession, taking into account the diversity of methods used.
• Contributions to Moose:
  • Optimize support for Python codebases within Moose.
  • Participate in the design and development of new Moose-based approaches to address specific industrial needs related to the data scientist profession.
• Scientific and Technical Support:
  • Contribute to experiments conducted by the EVREF team for the development of prototypes.
  • Participate in documentation, scientific publications, and user training.
  • Monitor technological advances in innovative software engineering approaches dedicated to development.

• Design and development of scientific software tools.
• Identification of needs and translation into robust technical solutions.
• Writing and presenting clear and precise technical documentation.
• Participation in scientific experiments, with contributions to associated publications.
• Active technology watch: exploration of new tools, frameworks, and methodologies related to software engineering and AI.
• Occasional training of developers and users on developed tools.
• Participation in thematic networks to share best practices in software engineering.

• Solid experience in software development (Python required, C++ and Java appreciated).
• Experience with Pharo.
• Experience in metaprogramming and metamodeling.
• In-depth knowledge of software quality assessment processes.
• Ability to translate industrial and scientific needs into robust technological solutions.
• Proven skills in technology watch: identifying relevant innovations for software engineering or data science.
• Excellent writing skills (technical documentation, scientific publications) in French and English.
• Ability to collaborate with various profiles (scientists, developers, industry professionals) in an interdisciplinary environment.
• Relevant experience in similar projects, preferably in the context of artificial intelligence and data research.

• Subsidized meals
• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities
• Access to vocational training
• Social security coverage

Selon profil