Machine Learning Engineer – Earth Observation Aiko

Overview Joining AIKO means becoming part of a young, talented team dedicated to delivering high-quality work while maintaining a healthy work-life balance. We believe in trust, responsibility, and flexibility, offering a supportive environment where you can thrive. Our team enjoys collaborating in our Torino office, working from home when desired, and taking time off when needed. Don’t miss the chance to revolutionize the future with us We are seeking a Machine Learning Engineer to join our growing and dynamic team. As a key contributor, you will play a crucial role in developing, implementing, and maintaining machine learning models, with a focus on computer vision and image processing for embedded systems. Your work will be instrumental in solving complexproblems and driving innovation in earth observation and AI-powered systems. You will collaborate closely with a dedicated Machine Learning team, tackling challenging projects involving data analysis and information extraction for real-world applications. With a focus on deploying deep learning models within hardware-embedded environments, your efforts will help build state-of-the-art AI integration for autonomous operations in the field of Earth Observation. You will also be pivotal in implementing modern MLOps approaches to streamline our development and deployment processes. Additionally, you will contribute to product development, working closely with cross‑functional teams to ensure that AI and ML solutions are aligned with user needs, product requirements, and overall system design. Your insights will help translate complex technical capabilities into practical, user‑focused products that advance our mission in Earth Observation technology. We value smart, motivated, and collaborative engineers who love solving problems and making a difference. Aerospace experience is not required—what matters most is your passion for technology, your drive to innovate, and your eagerness to contribute to cutting‑edge solutions in the future of space missions and beyond. Tasks Lead the development and deployment of machine learning models, with a focus on computer vision and image processing, ensuring seamless integration into hardware‑embedded systems. Design, implement, and maintain robust MLOps pipelines using tools such as Git, MLFlow, and Kubernetes to streamline model deployment and management in production environments. Collaborate with cross‑functional teams, including software engineers, data scientists, and hardware specialists, to develop and optimize ML applications tailored for embedded systems. Utilize Python, C++, and relevant ML libraries (e.g., Py Torch, Tensor Flow) 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. Contribute to product design process, providing technical insights and guidance to ensure ML solutions align with user needs and product goals. Continuously improve model accuracy and performance, applying best practices in software quality, version control, and testing. Disseminate results and insights effectively through internal presentations, documentation, and external publications, showcasing the impact of your work. Foster a culture of continuous improvement, driving innovation, and advocating for new methodologies and tools that enhance the company’s capabilities. Requirements Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Proven experience in machine learning with 3+ years in the role, showcasing a strong portfolio of expertise in developing deep neural networks, computer vision, and image processing. Proven experience working in product development teams, contributing to collaborative design, prototyping, and deployment of ML‑based products. Proficiency in Python, with additional skills in C++ considered a plus. Solid understanding of MLOps principles and hands‑on experience deploying models in production using tools like Git Lab, MLFlow, and Kubernetes. Strong statistical and analytical skills, with a solid grasp of machine learning theory and practical application. Experience with object‑oriented programming (OOP) and software development best practices. Excellent communication skills with the ability to present complex technical concepts clearly 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. Preferred Experience Ph D in Computer Science, Engineering, Mathematics, or related fields, highlighting advanced expertise in machine learning and its 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. Ability to integrate ML models into hardware‑embedded systems, ensuring efficient operation and optimal performance. Advanced knowledge of multispectral and hyperspectral image analysis, leveraging this data for machine learning applications in earth observation. 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. Benefits Ticket Restaurants Health insurance, on a CCNL insurance plan Welfare plan, according to CCNL Flexible working hours Flexible smart working policy Duvet day Wellness Package (Gym and Psychotherapy) Access to discounts with selected partners Access to courses for skills improvement Salary for the role: 35 K-45 K€ DEI in AIKO 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 #J-18808-Ljbffr