About the job
At Rossum, we leverage cutting-edge machine learning and a user-friendly interface to eliminate unnecessary paperwork, enhancing efficiency across the globe. Our ML Research Team is at the forefront of developing proprietary, state-of-the-art neural architectures that drive Rossum’s systems, processing millions of documents weekly for clients around the world.
We invite exceptional students to join our innovative startup in Prague, where we uphold the elite standards characteristic of Silicon Valley.
This internship is anything but ordinary. We seek motivated individuals with a background in ambitious research projects who desire the autonomy to manage their own initiatives while receiving guidance from our esteemed Research Team.
THE PROJECT: Your Innovation, Our Support
This is a 2-month summer internship in ML research with opportunities for long-term collaboration or a potential full-time position based on performance and mutual fit.
Your Role:
Join Rossum’s Research Team and spearhead your own project that explores state-of-the-art deep learning and LLMs for document understanding.
Engage in hands-on work utilizing Python and PyTorch in the realms of Computer Vision and NLP.
Conduct experiments on extensive real-world datasets that are integral to Rossum’s operational systems.
Gain access to advanced research servers equipped with numerous high-performance GPUs, terabytes of RAM, and hundreds of CPU cores.
Collaborate closely with senior researchers and engineers who are shaping the core technologies at Rossum.
After a successful interview, instead of merely assigning a task, we will tailor a project to align with your research interests and passions.
High-achieving interns may find their work integrated into production systems, influence internal research directions, and even co-author publications.
ABOUT YOU
You are a standout student with a keen interest in Machine Learning, Computer Vision, or NLP, likely in the latter stages of your Bachelor’s program or currently pursuing a Master’s or PhD.
You offer:
Practical ML experience through academic projects, internships, or research.
