Software Research & Development Engineer

About the Swiss Data Science Center (SDSC)

The Swiss Data Science Center (SDSC) is a national research infrastructure in data science and artificial intelligence (AI), founded by EPFL and ETH Zurich. Its mission - to enable data-driven science and innovation for societal impact - drives its initiatives in research projects, knowledge and technology transfer, and education. With a large multidisciplinary team of professionals in Lausanne, Zurich and Villigen, the SDSC provides expertise and services to various domains, such as health and biomedical sciences, energy and sustainability, climate and environment, and large‑scale scientific infrastructures. The SDSC also contributes to initial and executive education programs at EPFL and ETH Zurich. For more information please visit: www.datascience.ch.

About the role

You will work on one of the SDSC’s innovation partnerships in the French part of Switzerland. In this role, you will meet partners (companies) to understand their needs and help them define a high‑impact project with the SDSC. You will be responsible for successfully carrying out the project thanks to your machine learning expertise with the help and support of the SDSC team.

The Swiss Data Science Center (SDSC) is hiring a Software Research & Development Engineer to join its project‑based engineering team in Geneva, Lausanne, or Zürich. This team focuses on transforming research outcomes into production‑ready data science infrastructure. It operates in a complementary role to platform teams: exploring, building, and validating solutions before they are adopted as sustainable services.

You will work at the intersection of research and engineering, taking early‑stage ideas, prototypes, and emerging solutions, and turning them into reusable systems ready for real‑world deployment. This includes aligning with FAIR principles while going further: ensuring that what is FAIR is also usable, scalable, and sustainable in practice.

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.

Your tasks

• Contribute to projects that evolve through two complementary modes.
  • In early phases, engage in focused exploration and prototyping, shaping solution spaces, testing approaches, and making technical choices.
  • As projects mature, contribute to Minimum Viable Product (MVP) development, building operational, reusable components that can transition into production environments.
• Collaborate with engineers across the stack to build end‑to‑end solutions, contributing primarily to backend, data, and infrastructure components, while occasionally supporting lightweight user‑facing elements where needed.
• Ensure continuity beyond the project lifecycle by working closely with internal platform teams and partner IT units to transition successful MVPs into production, ensuring they are maintainable, transferable, and ready for operational use.
• 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: https://swissdatasciencecenter.github.io/best-practice-documentation/

Your profile

• Open to candidates across different levels of experience; early‑career or experienced, with emphasis on problem‑solving and collaboration.
• Enjoy building systems that work in practice, not just in theory. Comfortable navigating ambiguity, engaging with stakeholders, and iterating towards solutions.
• Care about quality, clarity, long‑term usability, and building systems that are secure by design and aligned with best practices.
• Background in software engineering, data engineering, or a related field, with interest in data‑intensive systems. Solid foundation in software or data engineering, typically developed through a Master’s degree or higher (e.g. PhD) in Computer Science or a related field, or equivalent professional experience. Experience in one of the application domains is a plus, but not required.
• Comfortable working at the interface between teams, helping bridge research, engineering, and operations, and ensuring that what is built can be successfully adopted and sustained.
• Experience with modern software and data engineering practices such as version control, testing, APIs, data pipelines, containerisation, reproducible workflows (e.g. Docker, CI/CD, Nix), and programming in languages such as Python, Go, Rust, or similar.
• Exposure to data modelling or semantic interoperability (e.g. ontologies, common data models) is a plus.
• Attitude, curiosity, and a drive to learn are valued; technical skills can be developed on the job.

We offer

• A stimulating, collaborative, cross‑disciplinary environment in a world‑class research institution
• Flexible work arrangements, including remote working, flexible time, condensed week
• Exciting challenges, varied projects, and plenty of room to learn and grow
• An opportunity to follow your passion and use your skills to make an impact on research communities and society
• A possibility to spark your creativity by experimenting and learning new technologies

Informations

• Contract Start Date: 01/06/2026
• Activity Rate: 80‑100%
• Contract Type: CDD
• Duration: 1 year, renewable
• Reference: 2166

Contact

We look forward to receiving your online application including a letter, CV and diploma(s). Applications via email or postal services will not be considered. For further information about the Swiss Data Science Center please visit our website: www.datascience.ch

Questions regarding the position should be directed to hrdatascience@datascience.ch with the job n° reference.

Remark:
Only candidates who applied through EPFL website or our partner Jobup’s website will be considered.

Files sent by agencies without a mandate will not be taken into account.