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Senior Geospatial Scientist at Matter Intelligence. Remote Location: San Francisco. About Matter Intelligence. Welcome to Matter, where we are building the future of vision AI: pairing a world-first sensor that sees molecular chemistry, temperature, and 3D shape with a Large World Model that will be the most powerful intelligence engine for our physical world. This system doesn't just see what something looks like; it understands everything from a single pixel. We call this Superintelligent Vision.. You'll join a team that has delivered technologies to Mars for NASA/JPL, co-founded and led infrastructure for OpenAI, designed cutting-edge sensors for U.S. Defense, and invented core algorithms for spectral and 3D imaging. We've come together to build the next infrastructure for vision and intelligence in the physical world.. About the Role. We are seeking a Senior Geospatial Scientist to lead the development of algorithms and data pipelines that transform our ultraspectral imagery into actionable intelligence. This role sits at the intersection of remote sensing science, machine learning, and scalable cloud infrastructure—turning raw hyperspectral data into validated, production-ready data products.. You will design and implement physics-informed ML algorithms, build robust AWS-based processing pipelines, and ensure the scientific validity of every output—from sensor physics through final data products. Your work will directly enable Matter's mission to deliver transformative Earth-observation capability across 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 for diverse geospatial applications.. Translate domain science (agriculture, mineralogy, ecology, aquatics) into validated algorithmic approaches.. Leverage modern AI tools to accelerate code generation and problem-solving.. Pipeline Architecture. Build and maintain scalable data processing pipelines on AWS to handle large-scale geospatial datasets.. Architect systems for radiometric correction, atmospheric compensation, and geometric orthorectification.. Optimize pipelines for throughput, latency, and cost across petabyte-scale imagery.. Scientific Validation. Evaluate the efficacy and accuracy of data products with rigorous statistical validation.. Maintain deep scientific understanding of all pipeline elements—from sensor physics to final output.. Design and execute calibration/validation campaigns using ground truth and reference data.. Team Collaboration. Partner with the Image Processing team to refine algorithms and support high-volume data processing.. Work closely with sensor engineers, systems engineers, and mission operations to ensure end-to-end data quality.. Contribute to technical proposals, publications, and customer engagements.. What Success Looks Like. Production-ready algorithms delivering validated data products at scale.. Robust, well-documented pipelines handling diverse hyperspectral workflows.. Clear scientific validation demonstrating data product accuracy and reliability.. Cross-functional partnerships enabling seamless sensor-to-insight workflows.. Qualifications. Required. PhD in a Geospatial-related field with 2+ years of experience, OR Master's degree with 5+ years of experience.. Proven experience processing hyperspectral reflectance data and developing associated algorithms.. Experience applying geospatial analysis in at least two distinct domains (e.g., Agriculture, Mineralogy, Ecology, Cryosphere, Aquatics).. Strong proficiency in Scientific Computing (Python, NumPy, SciPy, xarray, rasterio, GDAL).. Experience with AWS cloud infrastructure (S3, EC2, Lambda, Batch, or similar).. Deep understanding of math/statistics and geospatial fundamentals (coordinate projections, remote sensing instrumentation, GIS theory).. Demonstrated high proficiency in using LLMs (ChatGPT, Gemini, Claude) for coding productivity and workflow optimization.. Preferred. Experience with spaceborne or airborne remote sensing missions.. Familiarity with atmospheric correction models (e.g., MODTRAN, 6S, FLAASH).. Experience with deep learning frameworks (PyTorch, TensorFlow) for geospatial applications.. Track record of publications or patents in remote sensing or geospatial science.. Experience in rapid development or startup environments.. Location. This role is based in San Francisco, CA, with onsite presence required (temporary remote flexibility may be considered). Ability to travel to San Francisco Bay Area or El Segundo offices as needed.. ITAR Requirements. To comply with U.S. export regulations, applicants must be one of the following:. A U.S. citizen or national. A lawful permanent resident (green card holder). Eligible to obtain required authorizations from the U.S. Department of State. Employee Offerings & Benefits. At Matter, we believe in rewarding high performance and providing the support you need to thrive. Our compensation and benefits package includes:. Compensation: . Competitive total package based on experience.. Equity: . Early-stage equity package so you share directly in Matter's growth and success.. Health & Wellness: . 100% employer-paid health, dental, and vision coverage.. Growth: . Opportunities to expand into leadership, strategic accounts, or cross-functional roles as we scale.. Who You Are. You are a scientist-engineer who bridges deep domain expertise with production-grade software. You think rigorously about data quality, communicate clearly with both technical and non-technical stakeholders, and thrive in environments where your work directly shapes products that matter.