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Computer Vision & MLOps Engineer
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-Time
From the employer’s posting
What you’ll work on
Full postingDevelop and deploy computer vision models for medical image classification and segmentation
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 and monitoring
From the employer’s posting
Develop and deploy computer vision models for:
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
What you’ll bring
All qualificationsCore experience
- Strong computer vision background for medical images, mainly segmentation and object recognition
- Python data stack: TensorFlow, PyTorch, numpy, pandas, scikit-learn
- Kubernetes, Docker and Helm for deployments
- Hands-on experience with Argo CD and Argo Workflows for ML pipelines
- High level of English expression and comprehension
Preferred experience
- Experience in digital health and healthcare innovation
Qualification wording
Strong background in computer vision solutions for medical images.
Proficiency in Python data stack (TensorFlow, PyTorch, numpy, pandas, scikit-learn).
Experience with Kubernetes operators and custom resources.
Hands-on experience with Argo CD and Argo Workflows for ML pipelines.
High level of expression and comprehension of the English language.
Experience in digital health and driving innovation in healthcare is highly desirable.
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.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 3 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 3, 20263 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Artidis is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- Docker
- Kubernetes
- MLflow
- NumPy
- pandas
- PyTorch
- scikit-learn
- TensorFlow
Where the posting names them
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.
- Experience with Kubernetes operators and custom resources. - Proficiency in Docker containerization and multi-stage builds. - Advanced Git knowledge (branching strategies, workflows).
Technical Skills - DevOps & MLOps: - Experience with Kubernetes operators and custom resources. - Proficiency in Docker containerization and multi-stage builds.
- 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
Your next step
Complete your application on artidis-ag.breezy.hr. The employer’s form will show what is required.
Applying through Breezy HR
- No account needed.
Already applied? Track this application
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Basel, CH
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.