About the role
<p><strong>Duration:</strong> Minimum 6 months; ideally 9–12 months, depending on the candidate’s experience</p> <p>Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows and provides actionable insights to help businesses in a variety of industries. Join us, as we continue to expand, grow and innovate, and help take Scandit to the next level.</p> <h1>About the Internship</h1> <p>We are offering a research-focused internship aimed at advancing machine learning methods for complex visual understanding tasks. The project centers on deep learning architectures for image-to-sequence modelling, such as Transformers, attention mechanisms, and modern sequence and representation-learning frameworks, to address challenging and highly structured computer vision problems. This project contributes to long-term research efforts aimed at achieving even higher performance, robustness, and generalization in large-scale visual applications.</p> <h1>What you will do</h1> <p>You will work closely with experienced ML researchers and engineers on cutting-edge research at the intersection of computer vision and sequence modeling. Your work will include:</p> <ul> <li>Designing and experimenting with new ML architectures for structured visual data.</li> <li>Evaluating alternative modeling paradigms (e.g., encoder–decoder, hybrid Transformer models, sequence-based representations).</li> <li>Investigating techniques for improving robustness, generalization, and multi-view reasoning.</li> <li>Running systematic experiments, ablations, and error analyses to validate research hypotheses.</li> </ul> <p>This project provides opportunities for novel model design, extensive experimentation, and scholarly research. You will contribute to long-term innovation in our technology, with potential real-world impact for millions of users. An ideal position for experienced master’s students, PhD collaborations, or candidates preparing for a research career in industry or academia.</p> <h1>Who you are</h1> <p>MSc or PhD student in Computer Science, Machine Learning, Artificial Intelligence, or a related field with a strong research focus. Candidates should have a solid foundation in machine learning theory, neural networks, and computer vision.</p> <p><strong>Essential Skills:</strong></p> <ul> <li>Proficiency in Python and deep learning frameworks such as PyTorch.</li> <li>Practical experience designing, training, and evaluating neural networks, including CNNs and Transformer-based architectures.</li> <li>Strong analytical and problem-solving abilities, with the capability t