Senior ML Engineer - Computer Vision for Earth Observation

Build and scale computer vision systems for Earth observation. The core of the role is geometric computer vision on very high resolution satellite imagery: 3D reconstruction from stereo and multi-view data, and robust image matching and registration across sensors, viewpoints, and time. This is a balanced role: part applied research, part engineering, all impact.

What you'll do

• Drive geometric CV development: design, train, and iterate on stereo/multi-view 3D reconstruction models and image matching/registration pipelines for VHR optical imagery.
• Research to production: identify and adapt state-of-the-art approaches in 3D reconstruction, depth estimation, feature matching, and adjacent geometric CV.
• Tackle generalization head-on: close domain gaps in learned stereo across sensors, geographies, and acquisition conditions, including through synthetic data and sim2real transfer strategies.
• Contribute to semantic tasks such as segmentation, detection, and change analysis that build on aligned imagery and 3D reconstructions.
• Own EO data quality: standardization and preprocessing for high-resolution imagery, plus dataset-quality diagnostics.
• Build scalable pipelines: training and evaluation infrastructure across cloud and secure on-prem environments, with experiment tracking and reproducibility.
• Deliver production-ready components: robust inference interfaces, model packaging, deterministic evaluation, and monitoring.
• Collaborate with data annotation function, partner teams, and external researchers on findings and deliverables.

What you'll need

• Strong computer vision fundamentals and practical debugging/optimization skills.
• Practical experience in at least one area of geometric computer vision: stereo/multi-view reconstruction, depth estimation, or image matching/registration.
• Strong Python engineering fundamentals with deep experience with PyTorch, implementing and training deep learning models at scale.
• Strong understanding of ML experimentation, versioning, and tracking.
• Background in remote sensing, computer science, physics, or related field, or equivalent practical experience.
• Comfortable working with researchers and presenting findings clearly and efficiently.
• Eligibility to obtain a German security clearance (Sicherheitsüberprüfung).
• You take ownership, communicate clearly, balance deep research with practical delivery, and enjoy working with complexity.

Nice to have

• PhD in remote sensing, computer science, physics, or related field.
• Hands-on experience with satellite / remote-sensing imagery.
• Experience with synthetic data generation and sim2real / domain adaptation for geometric vision tasks.
• Broader geometric CV: structure-from-motion, SLAM / visual odometry, or neural 3D representations.
• 3D / photogrammetry tooling: NASA Ames Stereo Pipeline, MicMac, COLMAP; DSM generation.
• Experience deploying models under constrained compute or on edge devices.

What they offer

• Flexible working hours and hybrid work model.
• Collaborative and learning environment with internal workshops, knowledge sharing sessions, and hackathons.
• Office in Berlin Kreuzberg with free fruit, nuts, and drinks.
• Urban Sports membership and BVG subsidy, corporate pension program.
• Potential to participate in employee stock option program.
• Diverse and vibrant international environment.