Job opening

Machine Learning / ML Engineer

SkinVision /  Amsterdam (NL)

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Job description

The work is done as part of a small team, consisting of colleagues who are highly motivated to improve health care systems. We work in a challenging medical environment where determination and perseverance are as important as great ML skills and whew priorities can change quickly.
The ideal candidate can think out of the box and acts strategically to discern which problems are important, articulating to the rest of team their ideas and the impact they can have on our users., * Developing ML-based services (or extending and improving our existing services) that support our users in decision making.
* Iterate over the full life cycle of ML/data models: data analysis, data preprocessing, modelling, tuning, pipeline and productization.
* Analyzing existing data and understanding user needs.
* Devise strategies for collection of data when necessary.
* Collaborate with human experts to enrich data and quality control, prove effectiveness of the new services.
* Sharing experiments and results with technical and non-technical audiences showing the impact on our users.


SkinVision is on a mission to save 250k lives in the next decade by revolutionising the way we care about your skin. Our technology empowers people to manage their skin health, enabling an efficient connection between users and the health system through a sophisticated yet easy to use mobile application available for download on any smartphone. With over 2 million users since inception and more than 30k new users joining us every month, we are constantly looking to grow our team with professionals who are driven by purpose and are challengers by nature.


* 2 years of experience, preferably in a medical app or software as medical device (SaMD) or commercial setting. Or proven ability to develop ML based systems to solve real world problems.
* Background in machine learning, applied maths, statistics, computer science, data science or similar. Strong understanding of probabilities in real world decision making.
* Experience in Python and modern machine learning frameworks.
* Getting things done attitude.
* Able to deliver production ready components where applying good machine learning practice and proof are as important as the final accuracy.
* Motivated to work in a continuously evolving environment.
* Good collaboration and communication skills.

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