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 decision-makers 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 and machine learning-powered analytics to develop new technologies, drive revenue, power research, and solve our world’s toughest challenges.

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 are iterating 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.

The design and management of annotated datasets is a fundamental component in the development of computer vision models at Planet. Every analytic product is powered by a model that needs to be trained with large amounts of high quality training data. These training data typically consists of Planet imagery coupled with corresponding annotations of a particular geospatial feature (ships, buildings, roads, etc). 

In the Analytics Engineering team, we are looking for a contractor engineer to assist with the management of our annotated datasets. This person would help our machine learning engineers in all stages of the dataset development cycle: sample design, collection strategies, ETL scripting and model evaluation metrics.

Role responsibilities:

  • Actively participate in dataset design and sample selection with machine learning engineers
  • Use python scripting and command line tools to import and export data within our internal systems 
  • Prepare and format datasets to be ready for supervised ML training in our platform
  • Evaluate models against labeled datasets and compute performance metrics
  • Inspect and evaluate labeled datasets from external partners
  • Perform content inspections of the predictions of production models and report quality defects

Must-haves

  • Good foundations of geospatial information systems
  • Bachelor’s degree
  • Intermediate level of Python and Linux command line
  • Familiarity with most of the following libraries: NumPy, GeoPandas, Rasterio, GeoJSON and Shapely 
  • Familiarity with GIS desktop software (QGIS or ArcGIS) 

Nice-to-haves

  • Academic training in remote sensing or GIS
  • Experience with statistical data analysis 
  • SQL
  • Bash scripting

Some press about us:

Our CEO, Will Marshall's TED Talk

"Tiny Satellites ushering in the New Space Revolution" Bloomberg Businessweek

"The All-Seeing Eye in the Sky video" Bloomberg Businessweek video

"Planet And Rocket Lab Create Mission Patch To Honor Women In Aerospace" —Planet Blog

Join Us:

Planet is headquartered in San Francisco, California, Earth. If you are feeling inspired, check out our website www.planet.com/careers and apply. Be sure to include a cover letter to let us know why you think you’d be a good fit and feel free to mention anyone you have previously worked with at Planet.

We are committed to building a diverse team and encourage applications from people of all backgrounds.

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