Senior ML Engineer (f/m/x) - Computer Vision for Earth Observation - #2668408

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Requirements

Please note that this position requires work authorization for Germany.

Language: English - Fluent (C1)

• Strong computer vision and machine learning fundamentals (representation learning, supervision strategies, evaluation design) and practical debugging/optimization skills.
• Practical experience across multiple computer vision problem types (for example detection, segmentation, classification, change detection, or geometric vision such as 3D reconstruction and image matching), with real depth in at least one. This can come from remote sensing or from another imaging domain where these problems matter (robotics, autonomous driving, photogrammetry, AR/VR, medical imaging).
• Strong Python engineering fundamentals with clean, maintainable code, and 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 a related field, or equivalent practical experience.
• Comfortable working with researchers and presenting findings clearly and efficiently.
• Willingness to work on-site in Berlin and eligibility to obtain a German security clearance (Sicherheitsüberprüfung).
  
  

Activities

As a Senior ML Engineer, you will develop state-of-the-art computer vision systems that extract reliable information from large volumes of satellite imagery, across a range of tasks and all the way to production.

• Build vision models across tasks: design, train, and iterate on models for detection, segmentation, classification, change analysis, and geometric vision (3D reconstruction, image matching/registration) on VHR satellite imagery, with clear ablations and measurable performance improvements.
• Research to production: identify and adapt state-of-the-art approaches across computer vision and remote sensing (papers → prototypes → validated baselines), focusing on pragmatic wins under real constraints.
• Push toward the edge: bring models to constrained and embedded targets for LiveEO's Twinspector programme, using model compression, quantization, and optimization for on-device and onboard inference.
• Build scalable pipelines: training and evaluation infrastructure across cloud and secure on-prem environments, with experiment tracking, reproducibility, and systematic failure analysis across geographies and acquisition conditions.
• Deliver production-ready components: robust inference interfaces, model packaging, deterministic evaluation, and monitoring.
• Collaborate and communicate: work with the data annotation function on labeling guidelines and edge cases, with partner teams to turn model capabilities into validated deliverables, and with external researchers, presenting findings clearly and efficiently.
  
  

Team

You will join Sektion 4, our government-solutions product team. The team owns its roadmap, delivers funded R&D projects end-to-end, and sets its own technical direction while collaborating with internal data functions and external research partners.

About The Company

LiveEO delivers AI-powered Earth Observation insights that help organizations stay ahead of critical risks. From vegetation encroachment to third-party activity and deforestation exposure, we provide timely intelligence that accelerates response, lowers costs, and enables compliance at scale.

Click on "Apply" for details on the benefits, the team and the application process.