Data Engineer

At Cardiologs, our mission is to make tomorrow’s medical diagnosis efficient and accessible to everyone, anywhere, anytime. We leverage machine learning (AI) and cloud computing technologies to fulfill this vision. Our first product is a SaaS application to help physicians diagnose cardiac diseases, already deployed worldwide.

We are a tight-knit team and we nurture our company culture with monthly all-hands meetings and apéros, weekly yoga classes, climbing activities, daily coffee breaks in our comfy kitchen... But most importantly, we believe that a good atmosphere at work makes people more efficient on what they are best at!


What you’ll do


We are looking for an energetic Data Engineer to strengthen our Research Team.

You will be working on data processing pipelines from our ECG database all the way to the improvement of our machine learning models.

Your work will include development and maintenance of data pipelines for:

- selection of relevant ECGs from our database;

- assignment, gathering and quality control of expert annotation;

- training of our machine learning models;

- evaluation and validation of our models;

- handle user analytics from our platform.

Requirements

Who you are


  • An autonomous, committed, enthusiastic person with a "can-do", creative and challenging mindset
  • You have experience with Python, NumPy, Pandas or equivalents and you are eager to learn.
  • You have a solid understanding of Machine Learning good practices, experience working on machine learning algorithms in production is a plus.
  • You have experience with SQL databases and web APIs.
  • Fluent in spoken and written English, and have at least basic notions in French

Bonus:

=> You have previous experience and/or strong interest in developing healthcare products.

=> You already worked in a startup environment.


Our Recruiting Process


  • Introductory phone call with a quick technical test
  • Possible short Python homework
  • Technical interview
  • Performance interview
  • Culture interview with lunch (and/or drinks) with the team