About the job
Duration: Minimum 6 months; ideally 9–12 months, depending on the candidate’s experience.
At Scandit, we empower individuals with cutting-edge technology. Whether it’s accelerating delivery routes for drivers, ensuring patients receive the correct medications, or streamlining retail operations, our solutions transform workflows and yield actionable insights across diverse sectors. Join us as we innovate, expand, and elevate Scandit to new heights.
About the Internship
This research-oriented internship is designed to propel advancements in machine learning techniques for intricate visual understanding tasks. You will engage in projects that focus on deep learning frameworks for image-to-sequence modeling, including Transformers and attention mechanisms, to tackle complex and highly structured computer vision challenges. Your contributions will play a crucial role in our long-term research initiatives targeting enhanced performance, robustness, and generalization in large-scale visual applications.
Your Responsibilities
Collaborating closely with seasoned ML researchers and engineers, you will be at the forefront of groundbreaking research that intersects computer vision and sequence modeling. Your key responsibilities will include:
- Designing and testing innovative ML architectures for structured visual data.
- Assessing various modeling paradigms, including encoder-decoder frameworks and hybrid Transformer models.
- Exploring methods to enhance robustness, generalization, and multi-view reasoning capabilities.
- Conducting systematic experiments, ablation studies, and error analyses to substantiate your research hypotheses.
This internship offers a unique opportunity for original model development, extensive experimentation, and impactful scholarly work. You will help drive technological innovation with potential real-world implications for millions of users, making this position ideal for master’s students, PhD candidates, or those aspiring for research careers in academia or industry.
Your Profile
You are a Master's or PhD student in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline, with a strong emphasis on research. You possess a solid understanding of machine learning theory, neural networks, and computer vision.
Key Skills:
- Expertise in Python and deep learning frameworks such as PyTorch.
- Hands-on experience in designing, training, and evaluating neural networks, including CNNs and Transformer architectures.
- Exceptional analytical and problem-solving skills, with the ability to tackle complex challenges.

