Remote Sensing Machine Learning Engineer

We’re looking for a mission-driven Remote Sensing Machine Learning Engineer to develop proprietary AI/ML algorithms that extract advanced insights from multi-sensor satellite data.

Specific responsibilities will include:

• Designing and training deep learning models for object detection, segmentation, and classification on satellite imagery
• Processing and analyzing large-scale Optical, SAR, and hyperspectral data
• Optimizing ML models for deployment on cloud infrastructure (AWS/GCP)
• Collaborating with the remote sensing and data engineering teams to build scalable ML pipelines
• Utilizing Google Earth Engine and open-source tools for data preparation and analysis
• Those who are successful will progress quickly, either as individual contributors or following a management path.

We’re looking for someone who has:

• 3+ years of experience in Machine Learning, specifically applied to computer vision or remote sensing
• Strong proficiency in Python and deep learning frameworks (PyTorch, Tensor Flow)
• Experience working with multi-sensor satellite data (SAR, Optical) and Google Earth Engine
• Solid understanding of ML lifecycle, from data preparation to model deployment
• Cares deeply about the climate and ecosystems of earth
• Is a self-starter who thrives in constantly evolving environments, ideally with early-stage start-up experience