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About the Role:
- Combine deep technical expertise in computer vision with strong MLOps capabilities.
- Build and maintain production-grade AI systems for medical device and cloud deployment.
Key Responsibilities:
- Develop and deploy computer vision models for medical image classification and advanced segmentation.
- Design and implement end-to-end ML pipelines, managing the model lifecycle.
- Build and automate scalable MLOps infrastructure with monitoring and observability solutions.
Qualifications:
- Proficiency in Python data stack, deep learning frameworks, and OpenCV.
- Experience with Kubernetes, Docker, Argo CD/Workflows, and MLflow/Kubeflow.
- Strong communication skills and ability to work independently in a team.
What We Offer:
- Competitive salary and a bonus for outstanding performance.
- Challenging tasks, ownership opportunities, and a highly driven international team.
Artidis
Artidis is a clinical stage health technology company developing a nanotechnology platform for rapid tissue analysis to accelerate drug discovery and personalized treatment. It is a start-up with an intrinsically motivated international team, offering an agile environment and rapid advancement opportunities.