Our portfolio companies are always looking for great people. Apply to the opportunities below or send us your profile.

Senior Machine Learning Engineer at Kaia Health
Munich, DE
Kaia is a mission focused medical technology company:
In 2016 we set out with the mission to make effective, evidence-based therapies available to patients who suffer from chronic diseases. As back pain is the number one cause of disability worldwide with over 1 billion affected people, we built our first product, a clinically-proven mind-body therapy app, to help people with back pain.
At Kaia, we take proven offline therapy techniques and transform them into app-based therapies. However, in this process, some important aspects of these therapies can be lost. Our focus at Kaia Health AI Lab is to bring back those aspects by leveraging machine learning and computer vision. For example, our “Motion Coaching” technology allows users to get real-time feedback on how well they do their exercises. Motion Coach utilizes only the smartphone’s built-in camera and neural networks, and requires no additional hardware. Our app is the only one worldwide that can tell users if they are doing their exercises correctly. See trailer.
In the future, the AI Lab will also work on advancing our therapy personalization engine, as well as developing digital biomarkers for therapeutic purposes for our late-stage pipeline covering COPD, osteoarthritis, and Parkinson’s disease.
The role encompasses:
  • Build on our existing work and develop machine learning models for projects related to Human Action Recognition, Disease Monitoring and Prediction
  • Develop prototype models for machine learning use cases in health based on existing, large scale datasets and help integrate them into MVPs for user feedback
  • Build predictive models for production at scale
Your profile:
  • 3+ years experience in machine learning, preferably applied to Health Data or Timeseries Data 
  • Experience writing production level code in Python and experience with ML libraries (e.g. sklearn, NumPy, SciPy)
  • Experience with supervised and unsupervised learning algorithms, including cluster analysis, classification and regression with classical ML algorithms such as decision trees, XGBoost
  • Previous experience of shipping machine learning models to production 
  • Deep understanding of statistics, linear algebra, optimization and timeseries analysis
  • Strong system design skills and ability to base engineering decisions on product vision
  • Strong engineering background, knowledge of data structures, design patterns, software engineering best practices, and ML experiment documentation
  • Academic training in Computer Science, Software Engineering, Mathematics, Statistics, Physics or equivalent practical experience
Ideally you also have one of:
  • Domain expertise in chronic and progressive diseases, such as COPD or Parkinson’s disease
  • Experience with Advanced Signal Processing / Timeseries analysis techniques, e.g wavelet analysis, higher order statistics, chaos theory
  • Experience in collecting and building a dataset for health related tasks
  • Experience with Deep Learning algorithms and frameworks
  • PhD with published projects in the field of Digital Health 
You'll fit in with our company culture if you:
  • are user centric and view technology as a tool to improve a user’s life
  • have a bias for action; the world is complex and unpredictable place so starting, releasing, and getting feedback iteratively is the only possible path to success
  • strive to be articulate and humble, make the complex, simple, present ideas openly, accepting that being wrong is part of the process
  • are not afraid of tackling problems that others deem impossible
  • thrive in an entrepreneurial team, adapt easily to change, and enjoy a fast-paced environment
Some of the benefits we offer:
  • Directly shape the future of digital health
  • Work with serial entrepreneurs
  • Flat hierarchies, flexible vacation and working times
  • Mario Kart in the office :-) 

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