Telespazio

About the Company

Telespazio works to bring Space closer to Earth, benefitting citizens, institutions and companies in a variety of sectors ranging from design and development of space systems to management of launch services and in orbit satellite control; from Earth observation to integrated satellite communication, navigation and localisation services, and through to scientific programmes. Its open innovation approach, together with the cross-contamination of different operational domains and a constant focus on issues of environmental sustainability, allow Telespazio to operate in sectors that will become increasingly important in the years to come: from communication and positioning services for the Moon to management and monitoring of satellites and other orbiting objects (Space Domain Awareness), and creation of advanced in orbit services and satellite operation of drones and unmanned vehicles. Moreover, using innovations such as artificial intelligence and machine learning to process big data from satellites, Telespazio is in the front lines of development of space applications capable of improving people's lives on our planet and helping to win the great challenges of our times, such as the effects of climate change. Telespazio is a joint venture between Leonardo (67%) and Thales (33%) and one of the world's biggest suppliers of satellite solutions and services. The company teams up with Thales Alenia Space to form the parent companies' Space Alliance, a strategic partnership which offers a complete range of space services.

Founded in Italy in 1961, Telespazio is based in Rome and counts more than 3000 employees through its various subsidiaries and joint ventures.

Listed Jobs

Company Name

Telespazio

Job Title

Ingénieur.e en Intelligence Artificielle

Job Description

**Job Title** Artificial Intelligence Engineer **Role Summary** Develop AI and data‑science solutions for predictive maintenance and fault detection in critical satellite and space‑operations systems. Convert noisy, complex engineering data into actionable insights and decision‑support tools for operational teams. **Expectations** - Proven experience working with technical or industrial control systems, preferably in high‑availability or safety‑critical environments. - Strong applied data‑science skills: data wrangling, feature engineering, statistical modeling, and predictive algorithms (excluding image data). - Ability to analyze sensor streams, identify anomalies, characterize failures, and predict component life‑cycles. - End‑to‑end solution design: from data acquisition to model deployment and user training. - Proactive, intellectually curious, and comfortable engaging with multidisciplinary engineering teams. - Professional level English (technical writing and communication). **Key Responsibilities** - Acquire, clean, structure, and analyze raw telemetry and equipment data from critical space‑systems. - Perform exploratory data analysis to detect trends, anomalies, and failure modes. - Design and implement predictive maintenance and diagnostic ML models (e.g., regression, classification, time‑series forecasting). - Deploy models into operational pipelines, ensuring real‑time decision support for mission‑operations staff. - Conduct training sessions for operators on predictive tools and interpreting model outputs. - Collaborate across functional teams to integrate AI solutions with existing monitoring infrastructures. - Contribute to internal productivity improvement initiatives and continuous enhancement of data‑driven practices. **Required Skills** - Programming: Python (NumPy, Pandas, scikit‑learn, TensorFlow/PyTorch optional), Linux environment. - Data engineering: ETL, data cleaning, feature extraction, handling imbalanced or incomplete data. - Statistical & machine‑learning techniques: time‑series analysis, anomaly detection, survival analysis, predictive modeling. - Version control (Git) and basic DevOps for model deployment. - Excellent problem‑solving, communication, and teamwork abilities. **Required Education & Certifications** - Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical discipline. - Optional certifications in data science or machine‑learning (e.g., TensorFlow Developer, AWS AI/ML). ---

Toulouse, France

On site

09-03-2026