About this role
Summary: Build and maintain production-grade AI systems by developing computer vision models for medical imaging and implementing scalable MLOps infrastructure. The role involves optimizing models for deployment, managing the full model lifecycle, and ensuring robust monitoring and observability within a hybrid work envir...
About ARTIDIS
Artidis® AG is a pioneering clinical stage health technology company that aims to set the gold standard in tissue analysis and therapy optimization. By combining its nanotechnology platform for rapid tissue analysis with a holistic data solution, Artidis® accelerates drug discovery, tissue engineering, and personalized treatment. Artidis® focuses its research and development efforts on solid tumors to enhance responses to chemotherapy, immunotherapy, and cell therapies, driving precision in cancer care.
Job Purpose
This role combines deep technical expertise in computer vision with strong MLOps capabilities to build and maintain production-grade AI systems.
Duties
- Develop and deploy computer vision models for:
- Medical image classification
- Advanced segmentation
- Complex image analysis
- Implement solutions using deep learning and classical techniques
- Optimize models for medical device and cloud deployment
- Design and implement end-to-end ML pipelines
- Manage model lifecycle from experimentation to production
- Build, automate and maintain scalable MLOps infrastructure
- Implement robust monitoring and observability solutions
Qualifications
Technical Skills - ML & Computer Vision:
- Proficiency in Python data stack (TensorFlow, PyTorch, numpy, pandas, scikit-learn).
- Experience with OpenCV and other relevant computer vision libraries.
- Strong background in computer vision solutions for medical images.
- Expertise in developing and implementing computer vision solutions mainly image segmentation and object recognition.
Technical Skills - DevOps & MLOps:
- Experience with Kubernetes operators and custom resources.
- Proficiency in Docker containerization and multi-stage builds.
- Advanced Git knowledge (branching strategies, workflows).
- Experience Building and maintaining end-to-end ML pipelines.
- Hands-on experience with Argo CD and Argo Workflows for ML pipelines.
- Experience with infrastructure automation tools like: Helm charts for Kubernetes deployments.
- Experience setting up and maintaining CI/CD pipelines.
- Hands-on experience with model lifecycle management.
- Hands-on experience with MLOps platforms: MLflow, Kubeflow...
Professional Skills
- High level of expression and comprehension of the English language.
- Experience in digital health and driving innovation in healthcare is highly desirable.
- Commitment to writing documented, clear, efficient, and maintainable code.
- Ability to design and implement requirements with long-term objectives, scalability, and maintainability in mind.
- Proactive way of communicating and working.
- Ability to work independently and take ownership without extensive supervision.
- Strong team player.
Working Conditions
The environment is a typical start-up with an intrinsically motivated international team. Our company is an excellent place for rapid advancement and offers a promising opportunity to learn and share know-how in a very agile environment. The position requires the employee to go the extra mile when needed. We are looking for a team player who appreciates direct communication. The effort is rewarded with challenging tasks, the possibility to take responsibility, a highly driven team, and work serving a significant purpose. The job position comes with a competitive salary and a bonus for outstanding performance.