Job Description

OR-X

ML Ops / Data Infrastructure Engineer for Surgical AI 80 - 100 %

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Start of employment 01.02.2026 (Flexible), temporary
The Operating Room-X (OR-X) is a national unique research infrastructure and surgical translation center designed to advance surgical innovation. It combines a fully equipped, realistic operating room with an advanced digital ecosystem that supports ex-vivo surgical experiments, multimodal data acquisition, robotics, AR/VR systems, and high-performance AI computing.



A core element of OR-X is its newly established data infrastructure, which enables the synchronized collection, structuring, and streaming of multimodal surgical data through custom hardware interfaces, integrated middleware, and a high-performance computing (HPC) backbone. This infrastructure is already operational and forms the foundation for scalable development and deployment of surgical AI applications.



In parallel, the hospital together with the OR-X is building a new platform for robotic surgery and intelligent assistance, bringing together robotics, simulation, AI, and data science. Within this ecosystem, we are seeking a ML Ops / Data Infrastructure Engineer for shaping the underlying data, hardware, and computing infrastructure that enables machine learning, robotics, and real-time surgical AI across OR-X. The role focuses on bridging multimodal data pipelines, HPC systems, and real surgical workflows to enable reliable, real-time AI functionality in translational and experimental settings.

Your responsibilities

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MLOps & Model Integration

Deploy, monitor, and maintain machine learning models for surgical applications on HPC and edge devices within OR-X and ROSI research infrastructure Develop CI/CD pipelines for model lifecycle management, automated testing, and continuous deployment Leveraging NVIDIA technology for accelerating deployment of ML models Deployment of simulation environments

Data Engineering & Infrastructure

Integrate multimodal data streams (video, kinematics, tracking, imaging, sensor data) into the central AI infrastructure Develop APIs, data ingestion pipelines, and real-time streaming frameworks Structure and pre-process multimodal surgical datasets for model training and downstream analytics Develop a distribution strategy that enables external researchers to access the data

AI Deployment in Surgical Workflows

Work closely with AI researchers to operationalize models for surgical scene understanding, workflow prediction, skill assessment, and mixed reality Develop monitoring tools to ensure robustness, reliability, and latency compliance for real-time surgical applications Collaborate with robotics engineers to interface AI pipelines with devices accessible through ROS2 for control and visualization

System Testing & Validation

Support verification and validation experiments in realistic ex-vivo settings Implement performance monitoring, logging dashboards, and evaluation frameworks for deployed AI models Contribute to guidelines and best practices for safe, reliable clinical translation of AI-enabled systems

Your profile

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Degree from University of Applied Sciences or higher in Computer Science, Electrical Engineering, Robotics, or a related field Strong experience in MLOps, including Docker, Kubernetes, CI/CD pipelines, model serving and workflow orchestration tools Strong programming skills in C++, Python, and related languages Experience with data engineering, data pipelines, and multimodal dataset handling Proficiency in interfacing with AI infrastructures, preferably with experience in NVIDIA AI technologies. Experience with Holoscan is an asset Familiarity with Nvidia hardware (DGX, Spark, Jetson) Experience with ROS2 and real-time systems Comfortable in Linux/Ubuntu environments, Git/GitHub workflows, and containerization Motivation to work in a translational, interdisciplinary environment connecting AI, robotics, and clinical research English is the main working language; German is an added advantage

Information on your application

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What We Offer

Active participation in a rapidly growing and internationally recognized Surgical Data Science ecosystem The opportunity to shape the next generation of AI-driven surgical technologies, integrating AR, robotics, and intelligent assistance systems A highly innovative environment at the intersection of engineering, AI research, and clinical practice at the University Hospital Balgrist Collaboration with leading academic and industrial partners (ETH AI Center, NVIDIA, Microsoft, ZHAW, and others) A supportive, motivated, and interdisciplinary team that values creativity, collaboration, and impact


Application



Please send your application to Dr. Fabio Carrillo (fabio.carrillo@balgrist.ch) with the following documents:

Motivation letter (max. 1 page) Current CV Relevant project portfolio or GitHub (optional)

What we offer

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Work-Life Balance

Flexible working models (such as part-time positions, mobile working, job-sharing) Childcare at the kihz foundation of UZH and ETH

Learning and Development

Wide range of continuing education courses of UZH and the Canton of Zurich Language Center run jointly with ETH Zurich

Food

Food and drinks at reduced prices in the UZH cafeterias Lunch-Check-card with UZH contribution

Healthcare

Special conditions on the Academic Sports Association ASVZ Free seasonal flu vaccinations Rest and relaxation at the quiet room in the university tower

Discounts

Private traffic: Carsharing, rent a vehicle, parking space Digitalization: Hardware, software, mobile phone subscriptions Special conditions on hotel reservations

Conditions of Employment

Policies of the UZH Most UZH staff are employed according to public law

International Services

Support for people from outside Switzerland

Campuses

Campuses Zurich City, Zurich Irchel, Oerlikon and Schlieren Sites Zurich West, Old Botanical Garden, Botanical Garden and Lengg

Location

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OR-X

Forchstrasse 340, 8008 Zurich, Switzerland

Further information

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Questions about the job

Dr. Fabio Carrillo

Head of OR-X Research Unit
+41 44 510 32 64

Questions about the application procedure

Joelle Kunz

Assistant
+41 44 510 73 66

Working at UZH

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The University of Zurich, Switzerland's largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education. Put your talent and skills to work with us. Find out more about UZH as an employer!