Position Announcement – March 2021
Researcher and Software Developer – Deep Learning for Text and Impact Optimization
Full- or part-time positions in Vienna, Austria
Position Announcement (PDF, 900 kb)
Do you have a passion for novel solutions to challenging technical problems? We seek an outstanding candidate to join our R&D team in Vienna’s 9th district. Help us advance the state of the art in Scalable Semantic Systems, Artificial Intelligence, Deep Learning and Language Models.
Pursued together with leading media and technology partners across Europe, our research projects are supported by the European Union’s Horizon 2020 Programme and the Austrian Research Promotion Agency (FFG). As part of a dynamic and interdisciplinary team, you will participate in a fast-paced and innovative R&D environment and help deploy award-winning technology showcases together with major international organizations such as the United Nations Environment Programme and NOAA Climate.gov.
- Analytical skills, extensive software development experience (Python or Java),
- Good understanding of machine learning principles (training, validation, etc.),
- Deep learning frameworks and libraries (e.g., PyTorch, Tensorflow or Keras), ideally with a focus on Natural Language Processing (NLP) applications,
- Database systems such as PostgreSQL or CockroachDB.
- Experience in DevOps best practices, testing frameworks and CI/CD, bash scripting,
- Scalable content processing pipelines,
- Optimizing algorithms and architectures for stream processing,
- Automated deployment and testing of distributed architectures including continuous integration (GitlabCI, TravisCI) and container orchestration (Kubernetes, Docker Swarm).
We offer full-time, part-time (e.g., current computer science students) and PhD candidate positions. Salaries are based on qualifications and experience, e.g., EUR 44,000 gross per year (full-time, 40h) for candidates with a recently completed master’s degree. WU Vienna and webLyzard are equal opportunity employers and strongly encourage qualified women to apply. Please send your application including cover letter, CV and academic transcript to firstname.lastname@example.org (English or German, preferably as a single PDF file not exceeding 8 MB).