Software Research & Development Engineer

Software Research & Development Engineer

A national research infrastructure in data science and artificial intelligence (AI) of the ETH domain, Swiss Data Science Center (SDSC) supports academic labs, hospitals, industry and public sector stakeholders across domains such as health and biomedical sciences, energy and sustainability, climate and environment, and large‑scale scientific infrastructures.

The SDSC is hiring a Software Research & Development Engineer to join its project‑based engineering team in Zürich. The team transforms research outcomes into production‑ready data science infrastructure, exploring, building, and validating solutions before they are adopted as sustainable services.

You will work at the intersection of research and engineering, turning early‑stage ideas, prototypes, and emerging solutions into reusable systems ready for real‑world deployment, while ensuring adherence to FAIR principles and practical scalability and sustainability.

Projects are driven by concrete needs across domains such as health and biomedical sciences, climate and environment, energy and sustainability, digital society, and large‑scale data ecosystems.

Start of position
:
June 1, 2026 (negotiable)

• Contribute in two complementary modes: early‑phase exploration and prototyping, and late‑phase MVP development.
• Shape solution spaces, test approaches and make technical choices in early phases.
• Build operational, reusable components that can transition into production.
• Collaborate with engineers across the stack, focusing primarily on backend, data and infrastructure components while occasionally supporting lightweight user‑facing elements.
• Ensure continuity beyond the project lifecycle by working with internal platform teams and partner IT units to transition successful MVPs into production environments.
• Co‑design solutions with users and domain experts, participate in collaborative workshops, and iteratively refine requirements into robust implementations.
• Follow established engineering and data best practices with a strong focus on reproducibility, maintainability, interoperability and production readiness.

• Open to candidates across experience levels; approach to problem‑solving and collaboration is paramount.
• Enjoy building systems that work in practice, navigating ambiguity and iterating solutions.
• Concerned with quality, clarity, long‑term usability and secure design aligned with best practices.
• Background in software engineering, data engineering or related field, typically with a Master’s degree or higher (e.g., Ph.D.) in Computer Science or equivalent.
• Experience or interest in data‑intensive systems; experience in one of the application domains is a plus.
• Comfortable working at the interface between research, engineering and operations, ensuring successful adoption and sustainment.
• Familiar with modern software and data engineering practices: version control, testing, APIs, data pipelines, containerisation, reproducible workflows (Docker, CI/CD, Nix) and programming in Python, Go, Rust or similar.
• Exposure to data modelling or semantic interoperability (ontologies, common data models) is a plus.
• Valued attributes include attitude, curiosity, and drive to learn; technical skills can be developed on the job.

• A stimulating, collaborative, cross‑disciplinary environment in a world‑class research institution.
• Exciting challenges, varied projects, and room to learn and grow.
• Opportunity to follow your passion and use your skills to make an impact on research communities and society.
• Possibility to experiment with and learn new technologies.

EEO Statement:
Eth Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity, and nurture a working and learning environment in which the rights and dignity of all staff are respected. Sustainability is a core value – we are consistently working toward a climate‑neutral future.