Remote Sensing and Machine Learning Specialist

TierraSpec is an AI-driven platform optimizing soil health through satellite-powered solutions. We leverage machine learning and high-resolution satellite data to provide a cost-effective approach for sustainable soil management.

Position Overview: We are looking for an experienced Remote Sensing and ML specialist to process multi- and hyperspectral satellite imagery, develop efficient algorithms, and maintain data pipelines. You will work at the intersection of space tech, climate science, and agriculture to support our AI-powered soil intelligence platform.

Key Responsibilities

Algorithm Development: Develop efficient algorithms for processing multi- and hyperspectral satellite imagery, including anomaly detection and computer vision.

Machine Learning: Build predictive models for optimizing soil health using satellite data and in-situ observations. Develop and maintain ML pipelines.

Data Pipeline Engineering: Design and maintain ETL pipelines for satellite and field data, ensuring reliable processing.

Collaboration & Deployment: Work closely with multidisciplinary team to deploy models. Collaborate and support customers to ensure successful project outcomes.

Data Analysis & Visualization: Conduct analysis and create visualizations to deliver insights using tools like Pandas, NumPy, and visualization libraries.

Skills and Qualifications

Technical Expertise: Proficiency in Python and tools like Scikit-Learn, Pandas, GeoPandas, rasterio, and QGIS. Experience in remote sensing and image processing.

Machine Learning: Experience with ML tools like MLflow and Scikit-Learn.

Cloud: Experience with AWS; Azure DevOps or GitHub experience is a plus.

Project Management: Ability to manage cross-functional projects and client engagement.

Critical Thinking: Strong problem-solving skills in remote sensing and AI solutions for agriculture.