• Develop, implement, and optimize machine learning and deep learning models specifically tailored for, but not limited to, processing SAR data to extract actionable insights for geospatial and remote sensing applications.
• Utilize Python, C++, and relevant ML libraries (e.g., PyTorch, TensorFlow) to develop, train, and deploy deep learning models, emphasizing high performance and reliability.
• Manage and handle large datasets, ensuring efficient data preprocessing and analysis, storage, and access for ML model training and evaluation.
• Continuously improve model accuracy and performance, applying best practices in software quality, version control, and testing.
• Collaborate with SAR and Machine Learning teams to design algorithms for SAR data process and to optimize applications tailored for embedded systems.
• Process, analyze, and visualize SAR data, generating detailed reports, maps, and presentations for various stakeholders.
• Contribute to the development and deployment of machine learning models in production environments, leveraging MLOps approaches to ensure efficient integration and smooth operations.
• Work closely with cross-functional teams to deliver high-quality project outcomes, emphasizing accurate data handling, technical excellence, and adherence to deadlines.
• Stay updated on the latest advancements in SAR data processing, machine learning, and deep learning technologies, promoting continuous learning within the team.

• Master’s degree in Computer Science, Engineering, Mathematics, or related fields.
• Proven experience in machine learning and deep learning, with a focus on SAR data processing and analysis.
• Solid understanding of Synthetic Aperture Radar (SAR) operations, including data collection, processing, and interpretation.
• Proficiency in Python and relevant ML libraries (e.g., PyTorch, TensorFlow, Pandas, Scikit-learn) and familiarity with EO data analyses.
• Strong statistical and analytical skills, with a solid grasp of machine learning theory and practical application.
• Knowledge of GIS and EO concepts, including data management, projections, and visualization techniques.
• Experience with object-oriented programming and a commitment to quality and achieving project goals.
• Excellent communication skills with the ability to present complex data insights to both technical and non-technical audiences.
• A proactive approach to problem-solving, with a strong commitment to goals, quality, and a positive attitude toward growth and change.

• PhD in Computer Science, Engineering, Mathematics, or related fields, highlighting advanced expertise in machine learning for SAR applications.
• Proven track record in key technical or lead roles in R&D projects, particularly in innovative or cutting-edge technology environments.
• Experience in remote sensing, earth observation, and satellite data analysis, including expertise in processing imagery payload data and on-board data processing from cameras and various sensors.
• Expertise in designing and implementing MLOps pipelines using tools like Git, MLFlow, Kubeflow, and Kubernetes, ensuring efficient deployment of ML models.
• Deep understanding of the operational aspects of satellite systems, including challenges related to integrating ML models with embedded hardware and sensor data.
• Demonstrated success in managing and scaling complex ML projects from concept to deployment, with proven integration into real-world applications.
• Extensive experience in data management practices and the ML software development lifecycle, emphasizing quality, scalability, and efficiency.
• Familiarity with Scrum working methodology and Agile principles, demonstrating an ability to work efficiently within iterative and collaborative development processes.

• Ticket Restaurants
• Health insurance, on a CCNL insurance plan
• Welfare plan, according to CCNL
• Flexible working hours
• Flexible smart working policy
• Access to courses for skills improvement
• Salary for the role: 40K-60K€

Hiring Process: 

The interview process for this role will somewhat look like: 

• 1st Stage: Interview with our People & Talent and the Hiring Manager
• 2nd Stage: Technical step (live) and further video call to discuss it
• We hopefully make you an offer!

AIKO is an equal-opportunity employer. We encourage candidates from all  

backgrounds and experiences to apply. 

Research shows that women or people belonging to minorities often don't apply to  

roles they don't feel match 100% of the requirements. If this posting is  

interesting to you, we encourage you to apply even if it is not a perfect match! We are  

looking for real people, not robots!