Deep Learning Scientist/Engineer with focus on Remote Sensing at GAF AG
To support current and upcoming projects in the exciting field of satellite data processing, we are looking for a Deep Learning Scientist/Engineer with focus on Remote Sensing at our headquarters in Munich.
Our Earth Observation based portfolio is used worldwide by public authorities, companies and in scientific communities. With the help of our data analytics capacities we provide thematic and statistical information on various spatial reference levels globally. The processing of large amounts of satellite data with innovative analysis methods in cloud infrastructures has been indispensable for several years and enables e.g. the creation of products for land cover on a continental scale in the area of the Copernicus program of the EU.
- Developing together with your team members (Data Scientists/Machine Learning Scientists, Software Developers and DevOps Engineers) ML based data analytics workflows for the derivation of spatial data sets in raster and vector format based on satellite data and represent these to stakeholders such as project managers and customers
- Developing maintenance-friendly, effective, scalable Python code used in various projects
- Assisting in the transfer of prototypical software solutions for data analysis into applications that can be used in production environments
- Deploying code in different cloud environments and monitor/tune the applications for best performance
- Setting-up and administering scalable and user friendly AI tools, software or plugins
- Evaluating and assessing new technologies, frameworks or libraries and assessing them in terms of their benefit for the company
- Extending existing DL architectures, tailored to project requirements
- Contributing your own ideas and suggestions for improvement or new developments
What to expect:
- A job in one of Europe’s leading geo-service companies
- Variety instead of everyday routine in exciting geoinformation projects
- A friendly and respectful working atmosphere in an international, interdisciplinary and young team
- Working cross-functional with other teams according to agile principles
- Comprehensive support for your start at GAF (mentoring programme, German language courses)
- Learning and development – your experience and knowledge count
- Optional corporate pension, travel health insurance world wide
- Operational health management
- Great location in Munich or Neustrelitz with fabulous opportunities for outdoor activities
- Perfect connection to public transport
- And last but not least: Free coffee from our artisanal italian espresso machine (be your own barista)!
- A master’s degree in Science or Engineering, such as Geoinformatics, Remote Sensing, Computer Science, Data Science or similar
- Knowledge of Machine Learning fundamentals
- Theoretical understanding in -/and practical experience with deep learning applied to computer Vision. Experience in a remote sensing context is a plus
- Knowledge of more traditional Computer Vision techniques and libraries, e.g. OpenCV. (Always great for pre-post processing and sometimes getting a job done if DL fails)
- Python as your preferred programming language. Dabbling in compiled languages a plus
- Experience with the common data processing and machine learning libraries like scikit-learn, pandas and numpy
- Hands on experience with the common deep learning libraries such as TensorFlow, Keras and PyTorch
- English and German proficiencies
- Ability to think out of the box and work solution orientated
- Ability to work in a cross functional team with a broad variety of technical skills within an open and creative work environment
- Familiarity with databases, SQL/NoSQL
- Knowledge of geospatial libraries for Python, such as gdal/ogr, shapely, rasterio
- Experience with containerization
- Experience with cloud-based infrastructure such as Container, Openshift and AWS
- Academic track record/publications, interest in proposal drafting
Engagement from earliest possible date.
Would you like to work with us?
If you are interested in this career opportunity, please send your meaningful application including CV along with an indication of your salary expectations (gross) as well as your earliest entry date to firstname.lastname@example.org. Please use the keyword "Deep Learning Scientist/Engineer with focus on Remote Sensing" in the header of your e-mail.
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