AI Data Engineer (f/m/d)

Description

You will build reusable tools, run shared data infrastructure, and assess platforms for ultrasound teams across the world, within the Advanced Imaging Solutions business of the company.

The company makes medical technology, pharmaceutical diagnostics and digital solutions that help clinicians decide with more confidence and improve patient outcomes. It has over 100 years of healthcare experience and around 50,000 employees, and it works within a wider ecosystem aiming at precision health.

The role is based in Zipf, Austria, in a hybrid setup with at least 3 days per week in the office.

You will work with local teams and infrastructure owners to turn their requirements into tested solutions and help them adopt and run common tools.

Responsibilities

• Work with AI technical leads to turn cross-team requirements, reference architectures and priorities into working solutions and operating procedures.
• Plan and run reproducible experiments, proofs of concept and benchmarks on third-party and internal data management and AI development platforms, using real ultrasound team workflows.
• Evaluate functional fit, interoperability, performance, scalability, usability, integration effort and operating cost against agreed requirements, and document methods, results, limits and recommendations for platform selection.
• Work with individual teams to extend their internal tools for organisation-wide use, moving team-specific assumptions into configurable modules and standardising interfaces.
• Build and maintain shared libraries, services and connectors, with automated tests, versioned packages and deployment workflows that ease adoption and upkeep for other teams.
• Build and operate pipelines for ingesting, transforming and validating data that support curation, annotation, dataset preparation and AI development.
• Run agreed shared tools and environments day to day, covering configuration, updates, job monitoring, troubleshooting and performance tuning, in coordination with platform owners.
• Help teams onboard to the platform, integrate tools and migrate data or workflows, and give practical feedback on gaps in shared infrastructure.
• Add data quality checks, logging and traceability, and automate approved data access, de-identification and retention workflows with guidance from the responsible specialists.
• Investigate pipeline and platform failures, reproduce them, and work with internal platform teams or external vendors to fix root causes and prevent repeats.
• Write user guides, integration examples and operational runbooks, and provide training and technical support so teams can adopt, run and contribute to shared tools.

Requirements

• Expected: a Master's degree in computer science, data engineering, software engineering, information systems, AI or a related technical field.
• Expected: hands-on experience building and running data pipelines, shared software tools or AI development infrastructure.
• Expected: practical knowledge of cloud environments, containers, Linux and data workflow orchestration.
• Expected: strong Python and SQL skills, including designing APIs, integrating services and working with structured and unstructured data.
• Expected: experience with Git, automated testing, code review, continuous integration and delivery, and maintainable software packaging.
• Expected: the ability to design controlled technical experiments, benchmark platforms and explain results and trade-offs clearly.
• Expected: understanding of AI data workflows, including curation, annotation, dataset versioning, and training and validation data preparation.
• Expected: awareness of security, privacy and traceability requirements for healthcare data.
• Expected: fluent English and the ability to work with engineering, data science and infrastructure teams spread across the world.
• Desired: a PhD in computer science, data engineering, software engineering, information systems, AI or a related technical field.
• Desired: experience with medical imaging or ultrasound data and healthcare data formats.
• Desired: experience turning team-built software into reusable components that several teams adopt.
• Desired: familiarity with data catalogs, annotation tools, experiment tracking, model registries and AI development platforms.
• Desired: experience with infrastructure as code and observability, or with improving the reliability or cost of data processing.
• Personal attributes: collaborative and service-minded, willing to understand local team needs and contribute to shared solutions.
• Personal attributes: systematic and self-directed, careful about testing, documentation and dependable operation.
• Personal attributes: curious and adaptable, willing to learn unfamiliar platforms and improve tools based on user feedback.
• Applicants who do not meet every requirement are still encouraged to apply, since learning new topics and taking on challenges is part of the job.

Conditions

The role is hired in Zipf, Austria, in hybrid work with at least 3 days per week in the office.

Relocation assistance is provided.

Flexible working hours are available through flextime.

Benefits

• Compensation is set for the role and reflects your profile and experience, with a competitive salary and fringe benefits.
• In Austria the minimum pay must be stated: the annual compensation package starts at €75.000, and the effective salary will be discussed based on your qualifications and experience.
• A varied range of responsibilities in a growth-oriented company.
• An interdisciplinary team and an international work environment.
• An extra day off for your birthday.
• Free electric charging stations and ample parking on company premises.
• Good public transport access, plus a free company shuttle to Redl-Zipf train station, 2 km away.