WHO WE ARE
We’re a Berlin-based medtech startup dedicated to building AI-powered software that supports radiologists with their daily work: Analyzing medical images. Our first product mdbrain, which helps identifying Alzheimer’s and multiple sclerosis, is certified as a medical product and already has gained some traction in the German market. In order to scale further, we want to grow our software development team.
Our software is microservices oriented (Docker) and mainly written in Python (80%), with a React.JS frontend. Our systems architecture is hybrid on-premises and on the cloud (AWS). We automate as much as possible with our CI/CD pipeline (gitlab CI).
- Develop and test new features for our product, both independently and by doing pair-programming together with highly experienced developers from which you will learn a lot.
- Over time, take full responsibility for designing and developing new software components.
- Write automated tests, improve our test strategy and coverage.
- Write ETL jobs and help to maintain a huge database of medical images.
- Bachelor or Masters in Computer Science or similar.
- Passionate and talented programmer with a focus/interest in Python.
- Comfortable with Linux, command-line tools, SSH, bash scripting.
- Good understanding of the fundamentals of networking, REST APIs, microservices, AWS cloud.
- Fluent in English, basic/medium level of German.
Not needed, but a plus:
- Experience or interest in Machine Learning or image processing.
- Experience in IT-Radiology Systems.
- Knowledge of radiological data and systems e.g. DICOM format / PACS.
- You will join an early-stage venture which is trying to have an impact on people’s life and health.
- As part of a small team of engineers, you will have the chance to become a key employee and increase your responsibilities over time.
- We implement a flexible working culture (e.g. home office).
- You’ll find a friendly working atmosphere and will be able to take part in regular fun team-building activities.
- We enrich each other’s knowledge through periodical knowledge sharing sessions.