Flexible hybrid work (3 days remote, 2 days office)
Flexible working hours (core hours 10:00-15:30)
Application Deadline:
20.1.2026.
We're looking for a Machine Learning Engineer Intern to join our R&D team.
In the Research and Development department, you will be involved in a wide range of projects, from audio separation services for music content, intelligent document processing using artificial intelligence, applying data science and ML to healthcare domain data, to building data and metadata management solutions. Your work will include tasks such as training models for layout detection, section and labeled element recognition within documents, and information extraction. You will also participate in developing models for sensitive data recognition in the healthcare domain, such as MRI scans, medical histories, and urinary test results. This role provides an opportunity to collaborate with experts in a multidisciplinary team, solving real-world challenges using advanced machine learning methods.
Key Responsibilities
Data & Model Development
Collect, clean, and prepare data for training machine learning models
Prepare and execute experiments and train models
Study and implement existing machine learning algorithms
Evaluate and analyze machine learning model performance
Report results and visualize data
Research & Learning
Follow the latest trends and research in the machine learning domain
Stay up-to-date with new trends and technologies in AI
Study and apply state-of-the-art algorithms and techniques
Explore new approaches to solve complex problems
Collaboration
Participate in team meetings and provide support to senior engineers
Collaborate with cross-functional teams on research projects
Document work and share findings with the team
Contribute to technical discussions and brainstorming sessions
Required Qualifications
Proficiency in Python programming
Basic knowledge of machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch
Understanding of deep learning concepts
Knowledge of mathematics, linear algebra, and statistics
Excellent analytical and problem-solving skills
Strong communication skills and ability to document work
Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Physics, or related fields
Preferred Qualifications
Research experience in the field of machine learning
Experience with version control tool Git
Experience in Python and modules related to building REST APIs
Experience with PostgreSQL or MSSQL databases
Basic experience with the Hugging Face ecosystem
