Computer Vision Research Internship: Image to Sequence Modeling (e.g. Transformers)

About the role

Could your code give 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. This means we have no shortage of technical challenges for engineers like you. Join us, as we continue to expand, grow and innovate, and help take Scandit to the next level. "Everybody is welcome here" - Is a celebrated component of our DNA. At Scandit we strive to create an inclusive environment that empowers our employees. We believe that our products and services benefit from our diverse backgrounds and experiences and are proud to be a safe space for all. All qualified applications will receive consideration for employment without regard to race, colour, nationality, religion, sexual orientation, gender, gender identity, age, physical [dis]ability or length of time spent unemployed.

Responsibilities

• 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:
• Designing and experimenting with new ML architectures for structured visual data.
• Evaluating alternative modeling paradigms (e.g., encoder-decoder, hybrid Transformer models, sequence-based representations).
• Investigating techniques for improving robustness, generalization, and multi-view reasoning.
• Running systematic experiments, ablations, and error analyses to validate research hypotheses.

Requirements

• 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.
• Essential Skills:
• Proficiency in Python and deep learning frameworks such as PyTorch.
• Practical experience designing, training, and evaluating neural networks, including CNNs and Transformer-based architectures.
• Strong analytical and problem-solving abilities, with the capability to interpret experimental results and iterate effectively.
• Familiarity with research best practices, including reproducibility, controlled experiments, and ablation studies.
• Desirable Skills:
• Prior research experience in computer vision, pattern recognition, sequence modeling, or image-to-sequence architectures.
• Experience training large-scale models or working with foundation-style architectures.
• Contributions to publications, preprints, or open-source machine learning projects.
• Strong communication skills and the ability to work independently in a research-oriented environment.

Benefits

Additional Information

Duration: Minimum 6 months; ideally 9-12 months, depending on the candidate's experience 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. About the Internship 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.

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