Website Terra Cover
Terra Cover’s mission is to build solutions that help manage and mitigate the ever-growing water-related challenges for businesses and government agencies. We use satellite images together with advanced AI techniques to track changes in water availability across the globe. With support from the NSF (National Science Foundation), we are building a geospatial platform to monitor global water resources that will be used by Terra Cover partners.
Role: Applied Machine Learning Intern
We are looking for an applied machine learning scientist to work on our water monitoring platform. You will work with the lead machine learning scientist to develop novel physics-guided machine learning techniques to integrate satellite images from multiple sources to monitor water resources at high spatial resolution and temporal frequency. The platform will also use advanced uncertainty quantification techniques to integrate sparse ground observations with our satellite-derived observations effectively.
This opportunity will provide invaluable experience in working with petabytes of data on cloud infrastructure in a fast-paced environment of a startup company. Building solutions to socially and environmentally relevant problems requires close collaboration with the stakeholders. This opportunity will provide hands-on experience in communicating the science to stakeholders with diverse backgrounds.
- Graduate degree or pursuing a degree in computer science or data science.
- Experience developing/implementing complex machine learning models on large datasets (knowledge of uncertainty quantification methods is a plus!).
- Coding proficiency in Python.
- Experience in working with satellite imagery and cloud infrastructure is preferred but not required.
- Willing to work at the intersection of multiple disciplines with little guidance to solve complex problems from scratch and quickly learn new methods when needed to fill the knowledge gap.
- Passion for seeing research through from initial conceptualization to final application.
- Lead the development of Bayesian deep learning and multi-source data fusion models to combine multiple sources and incorporate uncertainty quantification within our water monitoring platform.
- Work closely with industry stakeholders to develop case studies and translate scientific research into operational products.
- Build effective strategies to evaluate model performance in different geographies and improve the robustness of the underlying machine learning techniques.
- Manage the processing pipeline to extract imagery data into machine learning compatible format.
This role is remote, but candidates based in Denver, CO, or Minneapolis, MN, are preferred.
Duration: 3 months – 6 months
- Competitive package in a disruptive startup
- Health/Dental Insurance
Note: Visa sponsorship is not available for this position. Successful candidates must be authorized to work in the United States.
To apply for this job email your details to firstname.lastname@example.org