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, and The Netherlands.
About the Role:
Our team is part of the Planetary Variables organization. We build the ML algorithms that transform Planet's imagery firehose into semantic data layers, such as cloud masks, land cover maps and change detection, usually deployed at a continental or global scale. Our team's core competence is the development of probabilistic inference algorithms that transform deep imagery time series into distilled maps of variables. These algorithms are typically a combination of computer vision (DL & non-DL) and time series, all cemented in statistical and physical principles.
In this role, you will join a team of engineers working together on algorithm development and integration into our distributed compute platform. You will perform exploratory analysis on remote sensing data and build models and inference pipelines on top of our infrastructure. You will also design ML operations to maintain the performance of deployed models and pipelines. Ideally, you have a strong background in applied statistics, a scientific mindset to conduct effective experiments, and solid experience with software engineering principles.
Our team is remote and distributed across North America, with flexible working hours. We make well-being a priority.
Impact You'll Own:
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