Senior Software Engineer, Geometry
Planet LabsAustria, RemotePosted 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, remote position based in Austria. If located near an office, you are expected to work from that 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 ... (truncated, view full listing at source)
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