Machine Learning Specialist

Tasks:

• Develop and implement machine learning models for space-related applications, such as satellite imagery analysis, anomaly detection in spacecraft telemetry and predictive maintenance.
• Collaborate with engineers, mission planners and software developers to integrate AI solutions into flight (and possibly ground) systems.
• Analyse large-scale, complex datasets from satellite sensors and onboard instruments.
• Optimize algorithms for performance, reliability and deployment in resource-constrained environments (e.g., edge computing on spacecraft).
• Monitor developments in AI and space research to incorporate the latest findings and innovations into our work.
• Ensure all solutions meet the safety, reliability, and cybersecurity standards required in aerospace systems.

Requirements:

• BSc, MSc or PhD degree in Computer Science, Aerospace Engineering, Physics, or a related technical field.
• Solid experience in machine learning and data analysis, with a strong grasp of both traditional and deep learning methods.
• Proficiency in Python and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
• Ability to think at system-level and work across multiple disciplines.
• Ability to work independently.
• Good problem-solving skills.
• Proficiency in English

Considered a plus:

• Experience with any embedded RTOS or Linux.
• Experience in embedded SW development and C/C++ programming languages.
• Experience working with satellite data, sensor fusion, or remote sensing is highly desirable.
• Familiarity with ISO and/or ECSS standards and aerospace simulation tools (e.g., STK, ESA/NASA data formats).
• Programming experience in scripting and automation.
• Any experience in FPGA and hardware development.

Location & onsite ratio:

• 50% onsite in the 11th district