About the job
About Matter Intelligence
Welcome to Matter, a pioneering company at the forefront of vision AI. We are developing an unprecedented sensor capable of perceiving molecular chemistry, temperature, and 3D structure, integrated with a Large World Model that serves as the most advanced intelligence engine for our physical environment. Our unique system not only captures visual data but also comprehends intricate details from a single pixel—what we refer to as Superintelligent Vision.
Join a team with an impressive track record, having provided technologies for NASA/JPL's Mars missions, co-founding and spearheading infrastructure for OpenAI, and crafting state-of-the-art sensors for U. S. Defense. Our collective expertise is dedicated to creating the next generation of infrastructure for vision and intelligence in the physical realm.
About the Role
We are in search of a Senior Geospatial Scientist to spearhead the development of sophisticated algorithms and data pipelines that convert our ultraspectral imagery into actionable insights. This pivotal role merges remote sensing science, machine learning, and scalable cloud infrastructure, effectively transforming raw hyperspectral data into validated, production-ready data products.
Your responsibilities will include designing and implementing physics-informed machine learning algorithms, constructing robust AWS-based processing pipelines, and ensuring the scientific integrity of each output—from the sensor physics to the final data products. Your contributions will directly empower Matter's mission to deliver transformative Earth observation capabilities across various industries.
Key Responsibilities
Algorithm Development
- Design and implement machine learning (ML) and physics-informed algorithms for hyperspectral data analysis.
- Develop spectral unmixing, classification, and regression models tailored to diverse geospatial applications.
- Translate domain-specific science (agriculture, mineralogy, ecology, aquatics) into validated algorithmic methodologies.
- Utilize modern AI tools to enhance code generation and accelerate problem-solving.
Pipeline Architecture
- Construct and maintain scalable data processing pipelines on AWS for handling extensive geospatial datasets.
- Architect systems for radiometric correction, atmospheric compensation, and geometric orthorectification.
- Optimize processing pipelines for efficiency in throughput, latency, and cost management across petabyte-scale imagery.

