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[Hiring] Machine Learning and Computer Vision Scientist Cloud to Street · Austin, TX

Cloud to Street is the leading flood mapping platform designed to protect the world’s most climate-vulnerable communities. By harnessing global satellites, advanced science, and community intelligence, we monitor worldwide floods in near real-time and remotely analyze local flood exposure at a click of a button. Our mission is to ensure that all vulnerable governments finally access the high quality information they need to prepare for and respond to increasing catastrophes. Founded by two women at Yale and seeded by Google, Cloud to Street is or has been used by governments across 15 countries. We are on track to enable new flood protection and insurance for 10 million people in the next 5 years.
We are looking for a best-in-class Machine Learning and Computer Vision Scientist to build tools for turning satellite data into actionable insights. You should apply if you are eager to develop scalable approaches to reducing the impact of catastrophic flooding and if you are excited to build an innovative and sustainable organization. In this role, you will take ownership of large projects in Cloud to Street’s machine learning and data science efforts. You will be building the full pipeline from data collection and creation to model testing and benchmarking. You will work with a team of scientists and engineers with expertise in remote sensing (optical and radar), hydrology, climate, social vulnerability, UX, and machine learning to turn petabytes of satellite data into meaningful information to empower the world’s most vulnerable communities.

Primary Responsibilities

  • Design ML-based solutions to problems facing the company, including but not limited to: flood detection, cloud detection, and gap filling (physically based inpainting)
  • Present findings in an accessible way to science and product teams
  • Integrate successful experiments and algorithms into C2S product
  • Utilize Google Earth Engine and the Google Cloud Platform tools to run algorithms and develop models
  • Visualize and explain work through presentations and notebooks *Work with with a team including a machine learning data fusion specialist, data engineer, Chief Science Officer, and Director of Technology and help grow the machine learning and data engineering team

Characteristics of a Successful Candidate

  • MSc or PhD in computer science, a related field, or equivalent experience (BSc with industry experience also considered)
  • Demonstrated ability to distill data into algorithms and results
  • Experience developing and deploying deep learning algorithms
  • Experience with a variety of machine learning techniques
  • Excited to tackle difficult research questions
  • Passion for developing technology to serve the most vulnerable

Useful Experience

  • Coding proficiency using Google Earth Engine JavaScript and/or Python APIs, and/or open source geospatial Python packages
  • Experience using machine learning to develop products or in industry
  • Experience with computer vision with imagery, especially with satellite imagery or using convolutional neural networks
  • Experience contributing to a shared codebase on GitHub with multiple collaborators
  • Using virtual machines on Google Cloud or similar platform
  • Working in disaster relief or in low or middle-income countries
Learn more about this role and apply here
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