ab sofort
Working Student (m/f/d) - AI Engineer
About Caire
At Caire.ai, we are building intelligent, contactless health monitoring solutions that enable medical professionals and patients to measure vital signs effortlessly through video-based technologies. As a growing MedTech startup based in Munich, we combine artificial intelligence, regulatory compliance, and medical expertise to deliver innovative software medical devices.
We are looking for a motivated Data Science / Computer Vision / AI Student (m/f/d) to support our AI team. If you’re passionate about Signal Processing and Deep Learning, eager to work on real world problems, and want to make an impact in a dynamic environment—this is the place for you!
Responsibilities
- Support with development of cutting edge AI Models for vital sign extraction
- Dive deep into explainability, confidence scoring in biological signal analysis
- Design and Supervise data acquisition procedures
- Help with model deployment and optimization
Qualifications and Skills
- You are currently pursuing a degree in a scientific or engineering field, ideally with a focus on deep learning, signal processing or computer vision. Self taught programmers are welcome as well.
- You have prior experience with Python, Pytorch, Docker
- You have a growth mindset and are willing to learn fast
- You are interested in solving hard but impactful problems
- You possess excellent English communication skills (written and spoken); German is a plus.
What we offer
- A learning-oriented environment where you can quickly develop your skills
- The opportunity to work in a fast-paced startup where your contributions have an impact from day one.
- A dynamic and international team with an office in a prime Munich location (Ostbahnhof).
- Hybrid working model with flexibility and autonomy.
Interested?
Send your CV and a short motivation letter to daniel.angloher@caire.ai with the subject line:
Working Student – AI
Caire Health AI GmbH
Caire develops an AI System that extract Vitalsigns from a video of the patients face. This works with any standard camera, so we turn any tablet, smartphone or webcam into a mobile health assessment tool.
Daniel Angloher
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