Machine Learning Engineer
vor 2 Wochen
About the Swiss Data Science Center (SDSC)
The Swiss Data Science Center (SDSC) is a strategic focus area of the ETH domain, with EPFL and ETH Zurich as founding partners, developing into a National Research Infrastructure in 2025. Its mission is to support academic labs, hospitals, industry and public sector stakeholders, including cantonal and federal administrations, through their entire data science journey, from the collection and management of data to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals across three locations (Lausanne, Zurich, 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. More:
Your mission
You will provide machine learning engineering expertise in the context of several SDSC partnerships in the French part of Switzerland. In this role, you will meet partners (companies, public sector entities, NGOs) to understand their needs and help them define a high-impact project with the SDSC. Together with the SDSC data scientists, you will be responsible for the societal and/or industrial impact of your projects thanks to your machine learning engineering expertise.
Main duties and responsibilities include
- Elaborate solutions that convert data science prototypes into impact in the context of an industry/public sector/NGO collaboration, with particular focus on the engineering side and in view of meeting production requirements
- Create original solutions with business partners, from solution design to industrialization
- Share expertise in machine learning engineering (and related fields) with fellow data scientists/machine learning engineers
- Presenting to a non-technical audience will also be part of your activities.
Your profile
The ideal candidate has:
- Master degree in Computer Science, Mathematics or similar field
- Good knowledge of machine learning concepts
- Demonstrated expertise in machine learning engineering, particularly in an industrial context
- Ability to present to various audiences
- Open to collaborative work and team spirit
- Highly appreciated: experience as a full-stack engineer, experience as a (data) architect, experience deploying LLM-based solutions in industrial contexts
- Fluent in English; knowledge of French highly appreciated
We offer
Do you see yourself helping Switzerland become more data-driven? Are you passionate about data science and with experience in machine learning? Are you keen to share what you know and get exposed to several projects in various domains? Are you eager to be part of a diverse and adaptable team with equal growth opportunities of its members at its core? If your answer to these questions is yes, you should consider joining us. Together, we can help move the Swiss landscape to the next level of data science.
During your time at the Swiss Data Science Center, you will benefit from the following opportunities:
- Develop your soft skills and meet with key stakeholders in several industries
- Interact with and learn from fellow data scientists
- Discover new data science applications in various industries
- Exchange on advanced machine learning topics with our academic experts
We actively promote a healthy work-life balance in the workplace. We are looking for candidates willing to contribute to an inclusive environment and eager to continuously learn.
Informations
Contract Start Date :
Activity Rate : 100.00
Contract Type: CDD
Duration: 1 year, renewable
Reference: 1877
Contact
We look forward to receiving your online application including application 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:
Questions regarding the position should be directed to with the job n° reference.
Remark:
Only candidates who applied through EPFL webstie or our partner Jobup's website will be considered.
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