Machine Learning Engineer

Job description


We are a health-tech company that provides image analysis for radiologists and neurologists dealing with acute stroke patients. Because of the time-critical nature of stroke care, our deep learning models need to be able to process 1GB-6GB head CT scans as fast as possible and deliver the AI results to the doctors anywhere and anytime. As our ML Engineer you’ll develop new algorithms in order to optimize our cloud-based platform StrokeViewer so the time to action for better healthcare improves. Not only that, it’s also important that the performance of our AI models and the number of AI experiments increase. On the other hand, you focus on how to decrease the time we spent running an AI experiment. This includes collaborating, not only with fellow engineers, but also with business, marketing, and our other departments.


  1. Improving AI algorithms that are already used by clients (retraining, fixing bugs)

  2. Organizing medical data that is used for training and testing

  3. Mastering a variety of backend tasks related to the AI algorithms that we develop

  4. Working on research projects together with radiologists

Job requirements


As an experienced machine learning engineer, you understand what it is to work with data, you’ll have to organize medical data that is used for training and testing. You are an experienced engineer that easily switches from brainstorming about brilliant solutions to designing and developing new features from the ground up. You understand that teamwork makes the dream work and easily switch from talking tech to talking business while retraining and fixing bugs in between.


  • >3 years of development experience

  • Delivering high standard, clean and well-tested code is your second nature

  • You’ve build cloud-native systems based on service-oriented architecture

  • Experience with Google Cloud Platform or AWS

  • Proficient in Python, Pytorch, SimpleITK

  • It’s a plus when you’ve worked with PytorchLightning, DVC, and MLFlow


  • Chance to make a real difference in patient’s lives
  • Pension contribution
  • 8% holiday pay
  • Flexible working hours
  • Travel expenses by car, train or bike
  • Work laptop (Apple or other)
  • Free lunch at the office
  • Stimulating environment with a fun, motivated and diverse team


My name is Elena Ponomareva. I grew up in Omsk, Russia, and studied Applied Mathematics in Saint-Petersburg. I got my master’s degree in Artificial Intelligence at the University of Amsterdam and after completing my thesis on skin burn segmentation I was looking specifically for an AI job in healthcare. That’s how I found NICO.LAB!

Why it’s so exciting to work at NICO.LAB? Because it gives the opportunity to help many people. The desire to help society unites me and my colleagues even more than common interests (those we also have), it makes us not just friends, but some sort of a family.

Moreover, it is also super interesting - working together with researchers from the University of Amsterdam and the Amsterdam University Medical Center, we are combining AI and medical knowledge to build not research-level, but production-level algorithms that can immediately improve the diagnosis and treatment of stroke patients.

I also like transparency and the flat hierarchy at NICO.LAB: everyone can share their thoughts and give feedback. That’s why working in this team is great, I really enjoy it.


We believe the combination of artificial and human intelligence will revolutionize emergency care and we work each day to make that happen. Founded in 2015 as a spin-off from the Amsterdam University Medical Center, our research background continues to drive our way of thinking. We have a diverse team from all corners of the world, composed of researchers, developers and experienced medical specialists who ensure our product and services match our clients' needs. We’re first tackling the major issue of stroke, the leading cause of life-long disability, where we will ensure every patient gets the right treatment in time. Watch more here.