ML Engineer - Generative Design applied to Mechanical Engineering

ML Engineer – Generative Design applied to Mechanical Engineering

The Swiss Data Science Center (SDSC) is a National Research Infrastructure jointly founded by EPFL and ETH Zurich and part of the ETH Domain .

Its mandate is to support academic labs, hospitals, the 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. In particular, in the Research team, we seek to accelerate the adoption of data science and machine learning methods within these diverse disciplines.

Project background

At the Swiss Data Science Center we work extensively in the application of machine learning to the fields of architecture and engineering. We have developed an open-source python library called AIXD ( ) for ML-assisted forward and inverse design. In the framework of an Innosuisse project with Accelleron Industries, we are currently exploring the application of these methodologies to more specialized industrial problems, as a way to accelerate the early design of high-end components. Specifically, we are investigating the application of inverse design methods to mechanical engineering, for the ML-based discovery of novel turbomachinery components. This involves implementing tailored ML models that exploit the unique characteristics of the problems at hand, as well as novel exploration and visualization tools that further facilitate the understanding of the results achieved.

To support the development of these methods, we are offering a one-year ML engineer position . The successful candidate will work hand-in-hand with the Senior scientists involved in the project, to help implement and evaluate new methods tailored for the design of turbomachinery components. This will also require tightly collaborating with the design engineers at Accelleron, in order to successfully implement models and approaches tailored to and are performant in this complex domain field. Furthermore, the successful candidate will have to propose and implement additional tools that allow end-users an efficient and intuitive utilization of the developed methods and models.

• Implement ML methods tailored to the design of turbomachinery components.
• Develop new visualization and exploration approaches that help understand the data and the results.
• Build interfaces between Accelleron configuration files and the AIXD toolbox.
• Support and conduct the software development of the toolbox by implementing new features, maintaining the code, creating tutorials, and documentation.

Profile

• You are a developer with a BSc or MSc in Computer Science or related fields.
• You have proven expertise in software development, especially with Python, solid understanding of industry-standard tools and best practices for software development, such as version control (Git), code review systems, automated testing, etc.
• You have experience in machine learning, deep learning and data science. Besides, you know how to implement data preparation workflows, including data cleaning, feature engineering, and exploratory data analysis.
• You have experience using Python libraries to carry out these tasks, such as PyTorch, SciKit Learn, etc.
• You know how to present complex results as appealing and informative plots.

We offer

• A 12-month ML Engineer position at 80%, at our SDSC Zürich office, conveniently located in Oerlikon.
• A stimulating, collaborative, cross-disciplinary environment in a world-class research institution, where you will be part of a team of 40 data scientists from more than 15 different countries. We all work towards applying and developing novel ML methods to solve real-world problems.
• We value work-life balance.
• We encourage experimentation and creativity by actively promoting the learning of new technologies and approaches on the job.

In line with our values , 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 our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Curious? So are we.

Interested in creating tools that will promote and universalize the usage of modern ML methodologies? Come and join our team!

We look forward to receiving your online application with the following documents:

• CV

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Questions regarding the position should be directed to (no applications).

Further information about SDSC can be found on our website, examples of projects carried out by the Research team can be found here.

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence. After receiving your application, we will do a pre-screening. If successful, one of us will contact you about the following steps and the selection process.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

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