Dida

Machine Learning Researcher (all genders) - Hybrid, Berlin

Dida · Berlin, Berlin, Germany

Software Development · 11-50 employees

Feb 27
Mid (2-5 yrs) Full-time Part-time Germany
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About the role

You will conduct machine learning research to improve methodologies in computer vision and natural language processing. Additionally, you will transfer theoretical insights into practical applications and publish your findings in academic journals or conferences.

What they look for

Machine Learning Deep Learning Computer Vision Natural Language Processing Mathematics Statistics Neural Networks Meta Learning Hyperparameter Search Research Algorithm Development

Requirements

Candidates must hold an MSc or PhD in mathematics, physics, computer science, or a related field. You should have a strong background in machine learning and deep learning, along with a track record of published academic papers.

Benefits

Flexible working hours Full and part time options Support for publishing research Collaborative learning environment

Full description

Your mission

You will

  • work on machine learning research projects, in particular addressing the question of how machine learning methodologies can be further improved in order to achieve better performances in relevant applications; those applications are likely to be connected to either computer vision or natural language processing, however, also more general methodological questions might be of interest (e.g. meta learning, hyperparameter search, efficient training of neural networks)
  • also work on transferring theoretical insights to practical use cases which are usually part of respective research projects, with the goal of setting new industry standards
  • be able to publish your results in relevant journals or at machine learning conferences such as ICML, NeurIPS or ICLR
  • foster our strong connections to academia, keep up to date with advances in machine learning research and actively take part in our company’s collaborative learning and development environment
  • support the dida team in applying cutting-edge machine learning algorithms

Your Profile

You have

  • a MSc or PhD in mathematics, physic, computer science or a related field
  • published academic papers; machine learning related papers are a plus
  • a creative mind that likes to solve problems
  • grounded knowledge about machine learning and deep learning in particular

Why us?

You will work with an interdisciplinary team of people with a solid background in mathematics and statistics. We offer flexible working hours (full and part time) and have a nice office with good coffee in Berlin Kreuzberg, close to Moritzplatz. We prefer a hybrid work model, but are open to remote work. We believe in science and support with publishing your research results. Here are short descriptions of some projects we have worked on. Estimate the amount of solar panels that fit on a roof (computer vision): Given a satellite picture and a ground image of a house, automatically detect certain elements of a roof (including obstacles, dormers etc.) in order to find out how many solar panels fit on it. This involves inferring 3d information from 2d pictures in order to infer the roof pitch. Detect, classify and suggest legal effectiveness of text paragraphs (NLP): Automatically go through thousands of legal documents with the goal to classify dedicated paragraphs and check their legal effectiveness. This involves converting scans to text, coming up with a labelling scheme (problem modeling), and detecting different paragraphs automatically, before tackling the inference task. What we need from you?

About us

dida is a machine learning software company with exciting problems for instance in computer vision and natural language processing. Our team tackles applied problems for different customers by using latest scientific advancements (especially in deep learning) and therefore believes that research oriented thinking can help solving real-world problems more efficiently.

At dida, we stand for equal opportunities, regardless of gender, nationality, ethnic background or disability. We encourage everyone, especially women, people of color, and people with disabilities to apply at dida.