Senior Software Engineer, Machine Learning

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:

Planet’s Built Environment applied machine learning team delivers advanced geospatial products primarily for external customers, with a focus on advanced analytics such as change detection, object detection, and emerging generative AI capabilities. This role is a blend of hands-on engineering and modeling: you’ll implement novel methods (e.g., deep learning for time series and computer vision), ensure best-in-class testing and validation, and deploy solutions to run at continental and global scales. You’ll collaborate with both data scientists and software engineers to drive innovation in remote sensing and large-scale geospatial analytics.

This is a full-time, remote position based in the United States.

Impact You'll Own:

• End-to-end model development & maintenance: Develop new algorithms or methods, implement and test them rigorously, and integrate them into production pipelines. Contribute to their ongoing maintenance and iteratively improve them.
• Advancing geospatial analytics: Innovate on computer vision, time series, and other ML techniques to uncover new insights from satellite and aerial data
• Cross-functional collaboration: Partner with product managers, data scientists, and engineers to define requirements, validate model outputs, and refine algorithms in iterative cycles
• Collaborating with adjacent ML and software engineering teams to ensure seamless integration of ML pre-processing and inference steps, defining best practices …