Machine Learning Engineer, Immuno-oncology

Kraków/ Remote

If you are passionate about computational modeling and would like to leverage your skills to help create breakthrough immunotherapies, we might have just the right role for you. You have a chance to join our interdisciplinary team of people devoted to their craft. You will help to develop innovative solutions in the area of cancer treatment. You will be using cutting-edge techniques, for example, to design immune cell receptors matching selected targets on cancer cells. We aim to create breakthrough immunotherapies by combining AI methods with bioinformatics, molecular dynamics, chemoinformatics, and immunological insights.

Job description
  • Working within an interdisciplinary team to productize computational models and analytical pipelines based on AI/ML/bioinformatics
  • Designing, implementing, and productizing computational approaches to challenging problems in immunology
  • Working within Ardigen’s R&D team, as well as with innovative companies and scientists worldwide
Key duties and responsibilities
  • Productize research results (tests, deployment, automation, transforming notebook analysis into python scripts, helping sustain best practices of Software Development)
  • Design, implement and run computational pipelines based on AI/ML/bioinformatics
  • Perform code review for AI/ML/bioinformatics-based solutions 
  • Help with choosing and deploying appropriate Data Science monitoring tools (e.g. MLFlow)
  • Advanced degree in Computer Science, Machine Learning, Mathematics, Statistics or relevant quantitative discipline
  • Strong programming skills in Python (numpy, pandas, sklearn, etc.)
  • Good programming practices (design, linting, testing, productization, etc.)
  • Knowledge of statistical and machine learning techniques (regression, classification, dimensionality reduction, clustering, feature selection, cross-validation, etc.)
  • Experience with deep learning libraries (TensorFlow, PyTorch, etc.)
  • Experience with distributed version control systems (Git or equivalent)
  • Good team player, good communication skills
  • Proficiency in English
You get extra points for
  • Experience in applying machine learning or bioinformatics solutions for Life Sciences
  • Experience with tools related to an efficient machine learning life cycle, such as Docker, Kubernetes, MLFlow, trains, kubeflow
  • Experience in cloud infrastructure (Google Cloud, AWS, etc.)
  • Experience in working along the principles of Agile
We offer
  • Solving challenging problems to contribute to breakthrough solutions in the fight against cancer
  • Room for a creative approach and freedom to use cutting-edge technologies and tools
  • Developing skills in an interdisciplinary and inclusive team of experts/scientists/engineers with passion for their craft
  • Participating in research and co-authoring publications and posters
  • Participating in training, conferences, etc.
  • Competitive salary and wide range of employee benefits (private medical care, Multisport card, life insurance, days with fruits, English lessons, volleyball and football teams)
  • Exceptional, well-resourced and comfortable working environment in a modern office
  • Working with innovative companies and scientists worldwide
  • A friendly, informal atmosphere and flexible working hours


We kindly ask you to add the following clause to your application: „I hereby express my consent to the processing of my personal data by Ardigen S.A. for the purpose of existing recruitment process”. If you want us to keep the submitted documents also for the purposes of future recruitment processes, we kindly ask you to add the following clause to your application: „I hereby express my consent to the processing of my personal data by Ardigen S.A. for the purpose of future recruitment processes for a period of 3 years from the date of submission of this document, in order to analyse them in terms of the recruitment processes carried out in Ardigen.”

We kindly inform you that only selected candidates will be contacted

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