ML Research engineer

Research engineers support our team by writing production-ready implementations of papers, testing and benchmarking algorithms and building software to solve shared problems.

The appliedAI Institute advances Europe by creating and disseminating expertise in Artificial Intelligence. We are Europe’s largest initiative for the application of cutting-edge trustworthy AI, leveraging Europe’s innovative power through education, research, and publications. We aim to be a fully transparent, open-source organisation, where everyone is invited to participate, discuss, and to engage with AI. As a non-profit, we create visions for Europe as a society, for us in a world of climate change and for our economy in the age of AI. We want to contribute to sustainable wealth through technology, to shape a world we want to live in.

The TransferLab aims to identify, test and disseminate established and emerging techniques in machine learning at multiple difficulty and novelty levels in order to provide practitioners and businesses with the best tools for their applications. We constantly survey multiple fields in ML, challenging and testing statements in the literature with the goal of distilling useful knowledge for the industry in the form of trainings, in-depth reviews, software playbooks, showcase applications and blog posts, but also fund and conduct novel research advancing the application of AI in industry.

Position overview

As a research engineer you will collaborate with and support different teams by:

  • conducting experiments for scientific publications,
  • designing and running benchmarks of recent papers,
  • contributing to or maintaining our or other open source projects,
  • identifying shared problems across projects to develop supporting software.

In order to do these things, both scientific rigour and good quality, maintainable code are a must: you will make design decisions affecting the quality and reproducibility of your team’s work, and you will be expected to find the right abstractions to improve our workflows and results, both at the algorithmic and infrastructural level.

As part of your work you will also watch for new and developing technologies of relevance for ML practitioners, applied researchers and yourself, and you will implement them within the Institute. Additionally, you will co-author scientific publications and participate in our seminars.

Your profile

We are looking for a machine learning engineer or experienced programmer with a solid understanding of the essential concepts in ML. You breathe Python and strive for readable, documented and maintainable code. Fundamental statistics, deep networks or parallelization in clusters (to pick a few random things) should all be familiar to you.

We welcome unusual profiles and career paths, but we find that people who can take on this role tick most of the following boxes:

  • A solid computer science background.
  • A very strong interest in technology and software development, and high quality standards.
  • Significant industry or open source experience, with an understanding of how complex professional software projects are run, including, but not limited to: version control in a team setting, continuous integration and delivery, thorough testing, etc.
  • Proficiency in Python. Experience with other programming languages would be beneficial.
  • Experience with ETL pipelines, data cleaning, SQL / NoSQL databases.
  • Good understanding of essential statistics and machine learning concepts.
  • Team player with a willingness to learn new things.
  • Fluent English.

It would be advantageous to have

  • Experience in writing on technical topics for a general audience (e.g. blog posts, magazine articles).
  • A Ph.D. in STEM, preferably Computer Science, Mathematics, Statistics, Physics or Electrical Engineering.
  • Experience contributing to open source projects.
  • Conversational German.

What we offer

  • Extended budget for attending conferences and buying books.
  • Possibility to work on cutting edge topics and publish papers and code
  • Possibility of remote work.
  • A highly motivated and dynamic environment, full of people who want to and can make an impact on Europe’s AI landscape.
  • A multilingual and multinational team of researchers, engineers, educational experts and strategists.