Mid Machine Learning Engineer (R&D Interactive Machine Learning)

12 000 – 18 000 PLN gross
contract of employment; full-time; hybrid

What you’ll do

You will be an integral part of our R&D Interactive Machine Learning Team that develops novel methods and solutions in domains of active machine learning and human based labeling. Your experience will be an asset to the team leader in key decision making. You will be co-responsible for machine learning components in one of our AI Solutions – Label in the Loop. Your day-to-day tasks will include working on ML libraries and extending their functionalities based on business needs-driven research that you will conduct.

In QED Software the R&D Teams work hand in hand with Engineering Teams to deliver commercial quality solutions as the final product. You will get a broad understanding of the products and work on their various aspects. Our in-house projects include aspects such as active learning, XAI, interpretable ML, AutoML, MLOps,  as well as big data processing and compression. Alongside this, we cooperate with partners in custom commercial implementations.

What you need to know

  • 3+ years of machine learning work experience
  • Deep understanding of machine learning (both in theory and in practice)
  • Experience in software development in line with the SOLID principles
  • Advanced Python and its open-source machine learning libraries (torch, numpy, scikit-learn, scipy and other)
  • Ability to develop tests in Python with common libraries like pytest or unittest
  • Effectively communicating complex ideas to both technical and non-technical people
  • Both Polish and English on communicative level

Nice to have

  • Relevant higher education (computer science, data science or other)
  • Active machine learning experience or willingness to learn it quickly
  • Experience in projects with elements of ML-human interaction
  • Ability to communicate concepts in data using visualizations
  • Familiarity with GitLab CI/CD Pipelines

What your tasks will be

  • Development and maintenance of ML libraries
  • Conducting business-driven research by experimenting with our solutions and performing the literature review
  • Summarizing completed tasks in a suitable form (report or documentation)
  • Code review and supporting colleagues in their daily work
  • Active participation and contribution to team meetings
  • Collaboration with third-party partners on specific implementations
  • Keeping up with the latest advances in the field of human based labeling

Feeling convinced? Apply!

Your benefits

Market-based salary adjusted to your skills

Private medical care

Multisport card

Flexible working hours

Internal trainings


10% time for self-development

Good coffee

The possibility of reconciling work and studies

Feeling convinced? Apply!