Senior Machine Learning Engineer at GmbH (Graz, Austria)


We are seeking an Senior Machine Learning Engineer to play a key role in ensuring our cutting-edge technology stays ahead of the curve.

You will research best practices, develop novel approaches, work on prototypes and evaluate what performs best. Whether you discovered a medium article or heard of a new function that is buzzing, have a closer look and see how it performs for us! You will experiment on a large scale on cloud infrastructure with high-end GPUs and TPUs.

In particular, you will:

  • Develop workflows and pipelines for faster and more efficient imagery annotation, model training, model deployment, and continual monitoring of computer vision algorithms
  • Integrate latest techniques from machine learning research (from supervised learning to generative models) into training and inference algorithms.
  • Contribute development to our scalable architecture to support our multi-source, geospatial analytics platform
  • Develop and deploy microservices for machine learning model inference
  • Mentor other members on your team with code reviews, design discussions, and new technologies
  • Collaborate with engineers from our platform and product engineering teams
Our Tech Stack:

  • Languages: Python3, C/C++, JavaScript
  • Deep Learning: Pytorch, Torchvision, CUDA, Horovod, Imgaug, scikit-learn
  • Image Processing: Numpy, OpenCV, SciPy, scikit-image, matplotlib
  • Data: PostgreSQL + PostGIS, SQLite, SQLAlchemy, GeoAlchemy, Alembic
  • Backend: FastAPI, Django, Dramatiq, RabbitMQ
  • Geospatial: GDAL/OGR, RasterIO, Geopandas, GeoServer, OWSLib, QGIS, ArcGIS
  • Version Control: Git, GitLab, Perforce
  • Continuous Integration: GitLab CI, Jenkins
  • Logging: Logstash, ELK
  • Frontend: Vue.js, OpenLayers
  • OS: Linux, Windows
  • Deployment: Docker, Kubernetes
  • Cloud Services: AWS, Azure, Exoscale
  • Task Management: JIRA
  • Knowledge Base: Confluence
  • Communication: Mattermost, Zoom


  • Passionate follower of the latest visual AI research with a detailed understanding of modern deep learning architectures and convolutional neural networks (CNNs)
  • Relevant degree from university / FH in a STEM field (e.g., computer science, machine learning, statistics, physics, engineering)
  • Proven ability to build scalable software operating on large datasets and with a high degree of task parallelism in Python (or similar language)
  • Experience in classic computer vision (2D image processing)
  • Python, Pytorch (or other deep learning frameworks), OpenCV, numpy, Linux / Bash
  • Fluent English skills (both written and spoken)
  • Self-motivated, ability to learn quickly and adapt to changes
  • Strong analytical and problem solving skills, including software debugging, and familiarity with the challenges of developing computer vision algorithms
  • Working experience with cloud computing platforms like AWS

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