Geospatial Data Engineer
Cloud to Street is the world’s leading remote flood mapping platform. We use global satellites and remote sensing AI to monitor flood risk and detect worldwide floods in real-time. Seeded by Google, we have been used by governments across almost 20 countries for disaster relief efforts. Partnering with top insurers, we are now launching the first commercial parametric flood insurance product to better protect climate-vulnerable communities.
We are looking for a Geospatial Data Engineer to help us scale up our deep learning efforts to turn optical and radar satellite imagery into actionable insights. In this role, you will take ownership of large projects in Cloud to Street’s Data Engineering agenda - building the full processing pipeline from training data collection to data labeling. You will work with a team of scientists and engineers with expertise in software engineering, remote sensing, machine learning and hydrology to turn petabytes of satellite data into meaningful information to empower the world’s most vulnerable communities.
This role is based in Brooklyn, NY and NYC area applicants are preferred. Remote work is possible within UTC -5 to UTC +1 time zones (Eastern Standard Time to Central European Time).
Send resume firstname.lastname@example.org with "Geospatial Data Engineer" in the subject line. Submissions should include an attached CV/resume and a paragraph of interest. Relevant past projects and/or publications are optional for submission.
Cloud to Street is devoted to building an inclusive and diverse company. Black, Indigenous, and people of color; women, queer people, and all gender identities, and individuals with disabilities are especially encouraged to apply.