Senior Machine Learning Researcher
Vor 5 Tagen
Satellite and drone imagery access is on the rise, and traditional image processing methods are struggling to keep up. We've never had more data, and yet it's never been harder to gain meaningful insights.
Our scalable AI platform enables custom model training on global features, providing real-time, on-demand geospatial insights with impressive speed and accuracy. The application turns months of manual work into mere minutes, and with much better results. We work with customers from various domains, from intelligence and defence, local and federal governments, insurance industry, to small and large enterprises, which requires us to have a lot of flexibility on how we deploy and maintain our services.
We kicked off in 2020 and have secured $35 million in series A funding from a lineup of top US and European investors, among which Microsoft M12, Point72 Ventures, Maxar, In-Q-Tel, SAFRAN, and ISAI/Capgemini.
We are looking for a Senior Machine Learning Researcher to join our team in Graz. You will be working on large-scale satellite and aerial imagery, developing models that detect and map buildings, roads, vegetation, and more.
Your Mission- Train and fine-tune state-of-the-art vision models for geospatial analytics.
- Research and implement cutting-edge ML architectures and workflows.
- Contribute to our no-code AI platform, where the users can easily train models themselves.
- Apply techniques such as foundation model adaptation, semi-supervised learning, and efficient model deployment.
- Strong grounding in machine learning / deep learning, especially computer vision.
- Experience with PyTorch, Python, and modern ML workflows.
- Experience with geospatial data, Earth observation, or large-scale AI systems.
- A curious mind and motivation to push technical and creative boundaries.
Please note that this job requires European working hours.
In accordance with Austrian legislation, we are disclosing the minimum remuneration fixed for this position is: 60.000,--€ gross per year. The effective salary depends on qualification and experience and may be significantly higher
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