MLOps Engineer for Autonomous Blood-Drawn Robot
Job opening for MLOps Engineer to own the ML infrastructure behind Europe's most advanced medical robot.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
MLOps Engineer – Python, AWS, PyTorch | Utrecht (MedTech / Robotics) [80K]
Ready to build and own the ML infrastructure behind one of Europe’s most advanced medical robots? This is your chance to work on real-time computer vision models that don’t just run in the cloud, but run on a physical device used directly in patient care.
My client is a fast-growing MedTech scale-up (~100 people, ~60 in engineering) developing the world’s first autonomous blood-drawing robot. They are in the final stage before market launch, with CE approval secured and solid funding through 2027. You’ll join the Sensing & Motion cluster (±15 engineers), the team responsible for the core vision, motion and robotics systems.
What you’ll do
You will own the MLOps infrastructure and tech stack behind their autonomous blood-drawing robot. This role goes beyond supporting models: you are responsible for building, automating, and maintaining end-to-end ML pipelines and ensuring the infrastructure is reliable, scalable, and production-ready. Rather than cloud-only systems, you work on real-time ML running on bare-metal / edge hardware inside the robot.
You design, own and continuously improve the full ML lifecycle, covering data management, annotation and training pipelines in Python and PyTorch, and deployment of models as ONNX to the robot’s local PC. Working closely with ML algorithm engineers, you translate research into robust, reproducible production tooling while acting as the bridge between ML engineering, connectivity and platform teams. AWS is used as a connected platform for pipeline orchestration and lifecycle management rather than a heavy data or training environment, with the focus firmly on owning and industrialising ML pipelines and infrastructure.
Your profile
- 4+ years of experience in MLOps / ML Engineering
- Strong Python engineering skills
- Proven experience owning and maintaining ML infrastructure and pipelines
- Comfortable automating end-to-end ML pipelines
- Experience with PyTorch; bonus if you know Docker or Kubernetes
- Experience with bare metal, edge, or on-device ML environments is a strong plus
- Hands-on with AWS as a connected platform (S3, CI/CD, pipeline integration)
- Self-directed, practical, and motivated to take full ownership of infrastructure in a regulated, robotics-heavy environment
What’s in it for you
A salary of €80.000, 8% holiday allowance, pension, 25 vacation days, hybrid working, full travel coverage, and visa/relocation support including the 30% ruling.
Interested? Contact me at sander@doghouse-recruitment.nl.