MLOps Engineer/AI Deployment Specialist
You will design, and implement the IT infrastructure for our new AI deployment pipeline. Working within our Pathology department, you will ensure that our advanced AI tools are integrated into daily workflows to enhance diagnostic precision and efficiency.
- Infrastructure Development: Build and manage a robust MLOps pipeline that connects our clinical IT system (SECTRA-PACS) with high-performance computing (HPC) resources.
- System Integration: Coordinate the flow of data from clinical systems through middleware components to containerized AI applications running on HPC clusters.
- Operational Excellence: Monitor, troubleshoot, and optimize the end-to-end AI deployment process, ensuring high reliability and performance.
- Collaboration: Work closely with IT specialists, AI researchers, and clinical experts to continuously improve and innovate our AI solutions.
We are looking for a proactive and technically skilled professional who thrives in a dynamic, interdisciplinary environment. You are someone who combines strong technical expertise with a passion for improving healthcare through innovation, and you are excited to build and design new IT tools.
You have:
- Have completed an applied science degree (i.e., HBO) or higher (i.e., master’s or PhD) in Computer Science or a related field;
- Experience with containerization technologies (e.g., Docker, Kubernetes) and distributed computing environments.
- Familiarity with message brokers and task schedulers (e.g., RabbitMQ, Celery) as well as modern DevOps/MLops practices.
- Proficiency in programming languages such as Python, and an ability to quickly adapt to new technologies.
- Experience in programming in Linux or UNIX environments, and software version control via Git and GitHub/GitLab.
- Excellent problem-solving skills and a detail-oriented approach.
- Strong communication skills and a collaborative mindset.
At Amsterdam UMC, you will be at the forefront of digital transformation in healthcare. We offer an environment where your expertise is valued, and your contributions directly improve patient care.
Our offer includes:
- Project expected to run for at least 2 years. We offer a standard 1-year contract with the prospect of a minimal 1-year extension.
- Classification in salary scale 10: €3.493 to €5.504 gross for full-time employment (depending on education and experience).
- In addition to a good basic salary, we offer an 8.3% end-of-year bonus.
- Vacation hours: 190,4 per year for fulltime and possibility to save additional hours.
- Pension accrual with the ABP, of which we pay 70% of the premium.
- A reimbursement of your public transport expenses. Do you prefer to come by bike? Then we have a good bicycle scheme.
- An active staff association and Jong Amsterdam UMC association, both of which organize fun (sports) activities and events.
Working at Amsterdam UMC means being part of a dynamic team dedicated to advancing healthcare through technological innovation. In our Pathology department, you will collaborate with experts from IT, AI research, and clinical care to implement AI solutions that make a real difference in patient outcomes. Specifically, you will be part of the AI core research team consisting of 5 PI’s and associated PhDs and research staff.
Amsterdam UMC has an open culture. This means that we hope that everyone feels welcome in our organization and that we strive to offer equal opportunities to everyone.
During the publication period, applications will be processed continuously. If the vacancy is filled, it will be closed early.
If you have any questions about this position, please feel free to contact Richard Schoonhoven, Assistant professor Multi-modal AI, via r.a.schoonhoven@amsterdamumc.nl
For more information about the application procedure, please contact Chella van Gelderen Recruitment advisor, via c.m.vangelderen@amsterdamumc.nl
A reference check, screening and hiring test may be part of the procedure. Read here whether that applies to you. If you join us, we ask you for a VOG (Certificate of Good Conduct).
Internal candidates will be given priority over external candidates in case of equal suitability.
Acquisition in response to this vacancy is not appreciated.