Geospatial Machine Learning Scientist
Vor 3 Tagen
The Landbanking Group’s (TLG) mission is to completely transform the way we use land in these unprecedented times of accelerating climate change, mass extinction and social divide. A novel, globally active company was founded to turn landowners and land stewards into producers and sellers of ecosystem services and products. TLG integrates various geospatial data sources and makes use of the latest machine learning (ML) models for earth observation (EO) data, carbon footprint and biodiversity analysis. Furthermore, metagenomics, fauna-sonics, open supply chain, and others enable us to develop digital twins of land plots, assess ecosystem quality, verify proof of impact and tokenize the claims so that they can be traded or bundled into tradable assets. TLG is now looking for a Geospatial Machine Learning Scientist (f/m/d) to join our ambitious team and help to develop and implement a large number of models to quantify ecosystem health and ecosystem services globally. **Your tasks**: - Design and train EO-driven machine learning models for automated monitoring of land-use practices and ecosystem health, e.g. mapping of hedgerows; crop types; trees in agroforestry; landcover etc. - Curate training data sets and design sampling strategies for ground data collection or custom labelling. - Package fitted models into containerized pipelines for deployment by the engineering team. - Stay up-to-date on recent developments in the fields of EO, ML and AI and feed back into internal model feasibility assessments and product roadmap planning. - A postgraduate degree or >3y working experience in geoinformatics, remote sensing, data science, environmental sciences, geoecology or similar disciplines - A solid understanding of common machine learning strategies (e.g. cross-validation, feature engineering, hyperparameter tuning) - Knowledge of supervised ML classification approaches for EO-data - Proven experience in deep learning based image segmentation and object detection on EO-data (PyTorch, Keras/Tensorflow) - Familiarity with standard geospatial tools (e.g. gdal, PostGIS, QGIS) - Some familiarity with Linux environments (e.g. docker, bash, AWS) **What's in it for you?**: - **Impact**: - A working environment based on trust, encouragement and feedback; positive, inspiring work atmosphere - High degree of autonomy - Competitive salary - Challenging and novel problems to solve - Work remotely (timezone should be close to Germany) - Plenty of learning and development opportunities within and outside our organization - Various employee perks including personal development budget
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