Machine Learning Engineer

4 days ago

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Agerpoint

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AgTech • Geiger-mode LiDAR • Permanent Tree Crops • Data Collection • Geospatial

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Description

• Welcome to Agerpoint • Agerpoint is reshaping how agriculture and nature field data is captured, analyzed and managed. • Building upon a decade of innovation and a deep IP portfolio, Agerpoint today brings technology to customers across agriculture, restoration and conservation using smartphones and tablets to affordably acquire ground truth data and uses automated analytics to extract plant measurements and insights. • Combined with other 3rd party data, this digital twin platform for crops and forests equips public and private sector organizations with unprecedented transparency across the food supply chain and protected natural environments. • The Agerpoint Capture mobile application allows users to capture 3D models of crops and trees via a smartphone or tablet, upload models to the cloud to assess health, yield, species, biomass, and more. • Customers can then derive insights from these models with Agerpoint Cloud, a spatial data platform that leverages machine learning for detailed plant-level insights. • Agerpoint was selected as a 2022 Technology Pioneer company by the World Economic Forum, recognized as one of the world’s most promising start-ups that are at the forefront of technological and business model innovation. • Agerpoint’s Know Your Carbon™ offering was selected as winner of the Carbon Market Challenge as announced at the United Nations COP26 Climate Summit. • The company is headquartered in Research Triangle Park, North Carolina at the Alexandria Center for AgTech - the country's first and only integrated multi-tenant, collaborative and amenity-rich R&D and greenhouse site.

Requirements

• Bachelor’s or Master’s degree in Computer Vision, Geomatics, Computer Science, or a related field preferred. • 3+ years of experience in geospatial development, GIS, and 3D modeling tools such as GARField and NeRF Studio. • Strong experience working with geospatial datasets, remote sensing data, and 3D data sources (e.g., LiDAR, satellite imagery, point clouds). • Proficiency with GIS platforms and tools such as QGIS, or similar. • Experience in 3D modeling, visualization, and geospatial analytics, particularly in agriculture and forestry applications. • Strong programming skills in languages such as Python, or C++ with libraries like GDAL, GeoPandas, and Open3D. • Excellent problem-solving skills and the ability to develop solutions to complex geospatial challenges. • Experience working in agriculture, forestry, or environmental monitoring industries is a plus. • Strong communication skills and ability to work in a collaborative, interdisciplinary environment.