DATA SCIENTIST

We are looking for a motivated Data / AI Scientist to join our project. In this role, you will play a key part in designing, developing, and industrializing advanced AI and Machine Learning solutions for critical systems across defense, civil aviation, and aerospace sectors.

As an active contributor to an agile team, you are expected to be a force of proposal, adaptable to change, and committed to translating operational needs into tailor-made algorithmic solutions to ensure the successful "Build & Run" deployment of high-impact AI use cases.

Key Responsibilities

• Participate actively in ideation workshops with internal stakeholders and external clients to identify operational needs and design custom algorithmic AI solutions.

• Rapidly analyze complex datasets to select, develop, test, and validate the most relevant ML/DL models adapted to specific use cases and sensitive data constraints.

• Implement end-to-end Machine Learning pipelines, from data collection and feature engineering to production deployment and monitoring (MLOps).

• Effectively communicate model objectives, performance, and business value to both technical teams and non-technical decision-makers.

• Actively share insights, best practices, and technological breakthroughs across the AI Center of Excellence to enrich collective knowledge and support organizational growth.

• Prepare technical documentation and ensure strict adherence to cybersecurity, data sovereignty, and ethical AI standards.

Engineering Skills

• Solid practical experience (5 to 7 years minimum) in AI and Machine Learning engineering.

• Proven track record of deploying end-to-end ML solutions into production, from initial data collection to end-user deployment.

• Strong ability to design robust algorithmic solutions and data architectures suited for critical systems and real-time operational constraints.

• Demonstrated experience participating in or leading client-facing workshops and technical ideation sessions.

Technical Skills

• Advanced knowledge of statistics, Machine Learning, and Deep Learning algorithms.

• Hands-on experience and understanding of RAG and MCP principles.

• Deep proficiency in Python and mainstream AI/DL frameworks (TensorFlow, PyTorch); exposure to Java, Spark, or Scala is a plus.

• Solid understanding of database technologies and SQL (with exposure to NoSQL systems).

• Practical experience with MLOps tools (MLflow) and modern development environments (GitLab, Docker, CI/CD).

• Familiarity with data security, privacy, and sovereignty constraints in defense or critical infrastructure environments.