<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p><strong>Company Description</strong></p><p>SERINO is a Munich-based deep-tech startup building the next generation of molecular sensing systems. Our mission is to bring laboratory-grade material analysis into real-world environments through a compact, software-defined sensing platform powered by printed infrared quantum sensors and physics-aware AI. By combining advanced semiconductor innovation with machine learning, we transform complex spectral signals into fast, actionable insights for both human operators and intelligent machines.</p><p>Our sensor-AI co-design approach enables precise spectral reconstruction without relying on bulky optics, filters, or complex mechanical alignment. This makes our technology highly scalable, portable, and cost-effective for applications across agri-food, pharma, recycling, textile, industrial inspection, and beyond. At SERINO, we are building a future in which molecular intelligence becomes accessible anywhere decisions need to be made. </p><p><br/></p><p><strong>Role Description</strong></p><p>This full-time, on-site role in Munich is for a Machine Learning Engineer who will contribute to the development of advanced AI models for sensor intelligence, spectral reconstruction, and data-driven material analysis. You will work on designing, training, and optimizing machine learning algorithms that convert raw sensor data into reliable and interpretable outputs for real-world applications.</p><p>Your responsibilities will include developing and evaluating machine learning models, analyzing experimental and application-specific datasets, improving inference and calibration pipelines, and collaborating closely with cross-functional teams across hardware, sensing, software, and product development. A strong interest in emerging technologies at the intersection of AI, sensing, and semiconductors is essential.</p><p><strong>Qualifications</strong></p><ul><li>Competence in Pattern Recognition and Neural Networks for image processing and data analysis</li><li>Strong foundation in Computer Science, including algorithms and data structures</li><li>Proficiency in Statistics and Mathematical Modeling to support model development</li><li>Familiarity with designing and implementing efficient Algorithms for machine learning tasks</li><li>Experience with machine learning frameworks such as TensorFlow or PyTorch</li><li>Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field</li><li>Excellent problem-solving skills and the ability to work collaboratively in a multidisciplinary team</li><li>Experience in the optical imaging or semiconductor field is a plus</li></ul> </div>