Senior Software Engineer, Geometry

Planet Labs
Berlin, GermanyPosted 16 March 2026

Job Description

Welcome to Planet. We believe in using space to help life on Earth. Planet designs, builds, and operates the largest constellation of imaging satellites in history. This constellation delivers an unprecedented dataset of empirical information via a revolutionary cloud-based platform to authoritative figures in commercial, environmental, and humanitarian sectors. We are both a space company and data company all rolled into one. Customers and users across the globe use Planet's data to develop new technologies, drive revenue, power research, and solve our world’s toughest obstacles. As we control every component of hardware design, manufacturing, data processing, and software engineering, our office is a truly inspiring mix of experts from a variety of domains. We have a people-centric approach toward culture and community and we strive to iterate in a way that puts our team members first and prepares our company for growth. Join Planet and be a part of our mission to change the way people see the world. Planet is a global company with employees working remotely world wide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands. About the Role: As a Senior Software Engineer on the Calibration and Validation (CalVal) team , you will be a key contributor to the integrity and evolution of our geometric models. You will design and implement the automated, scalable processes required to ensure our products consistently exceed rigorous geometric specifications and SLAs. You will develop photogrammetric models, error budgets, and calibration concepts for our high-resolution and next-generation monitoring programs, ensuring spatial integrity across diverse fleets. Additionally, you will drive ongoing performance characterization and serve as a lead investigator for complex image quality issues—troubleshooting sensor models and geometric anomalies to architect the long-term fixes that maintain Planet's high standard of spatial data. This is a full-time, hybrid role which will require you to work from our Berlin office 3 days per week. Impact You’ll Own: Perform ongoing space imaging operations, geometric calibration activities and performance characterization Design and implement automated scalable processes to calibrate hundreds to satellites to ensure that our products meet and exceed specifications and SLAs Collaborate within a cross functional team to develop performance models, error budgets and calibration concepts for new very high resolution constellation Troubleshoot geometric image quality issues and developing long-term mitigations and fixes What You Bring: 10+ years of industry experience with statistical processing and analysis techniques of large sets of measurement data Bachelor’s degree in Photogrammetry, Engineering, Physics, or Mathematics, relevant to geometric characterization of space imaging platforms Hands-on, can-do attitude, great interpersonal skills, and ability to collaborate effectively Understanding of end-to-end image processing chain – from sensor electronics and image ancillary data to geometric characterization Passion for Programming, Photography, Remote Sensing, Earth Sciences, and Geography Extensive experience leveraging scientific computing using Python in a Unix/Linux environment Knowledge of how to scale code with cloud computing resources, e.g. AWS or GCP Practical experience in solving problems by exploiting large cloud-based datasets What Makes You Stand Out: 5+ years remote sensing experience + track record of software automation of analysis of imagery/maps Master’s degree or PhD in a relevant scientific/engineering field Hands-on experience with calibrating and operating very high resolution optical satellites Familiarity with design and construction of imaging/capture/camera hardware Active contribution to open source projects Application Deadline: June 11, 2026 by 11:59p / 23:59 CET (Central European Time) ... (truncated, view full listing at source)
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