Austria onlySatellite 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 harder than ever 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, to small and large enterprise 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're searching for a Software Engineer to join our ML Training & Inference team, where you'll build the orchestration layer that powers our geospatial AI platform. You'll work at the intersection of distributed systems and machine learning, enabling customers to train custom detection models and run inference at scale on imagery spanning continents.
What you'll do
- Build and optimize ML orchestration pipelines that coordinate model training and inference across distributed worker pools
- Design resilient, high-throughput services that process terabytes of geospatial imagery through GPU-accelerated inference
- Develop the APIs and abstractions that allow customers to chain, filter, and compose AI models for complex detection workflows
- Collaborate with ML Researchers to put new models in production
- Tackle memory optimization, GPU autoscaling, and resource scheduling challenges unique to large-scale imagery processing
YOUR PROFILE
- Strong practical knowledge of Python with experience building production systems
- Experience designing and operating distributed systems or data pipelines
- Familiarity with async processing patterns, task queues, and worker pool architectures
- Solid understanding of PostgreSQL and data modeling
- Strong software engineering fundamentals: testing, CI/CD, observability, reliability
- You're outcome-oriented and comfortable navigating ambiguity to deliver results
- Experience with ML infrastructure, model serving, or training pipelines
- Hands-on experience with Kubernetes in production environments
- Familiarity with GPU workloads and the unique challenges of ML at scale
- Experience with geospatial data formats (GeoTIFF, COG, STAC) or imagery processing
- Background deploying systems in regulated or air-gapped environments
Ideally:
Tech Stack
- Python, FastAPI
- PostgreSQL, Redis
- Docker, Kubernetes (EKS, K3S)
- AWS (with on-prem and edge deployment targets)
- GPU infrastructure for ML inference
Why join us?
- Real impact at scale: Your work powers AI inference across imagery of entire countries, supporting defence, intelligence, and humanitarian applications
- Diverse deployment challenges: Build systems that run in AWS, on customer infrastructure, or on a laptop in the field—each with unique constraints
- Growth trajectory: Join ahead of our Series B as we expand into new markets and scale the platform
- Strong technical culture: Work alongside ML Engineers, GIS specialists, and infrastructure experts solving novel problems in geospatial AI
- Healthy work-life balance with flexible working arrangements
- Competitive compensation with personalized benefits including learning opportunities, mental well-being programs, and healthcare
The minimum salary is 56.000,--€ gross per year. The effective salary depends on qualification and experience and may be significantly higher!
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