Job Description

• Develop ready-to-use production grade geospatial AI models, tools, and solutions. 
• Integrate ArcGIS with popular deep learning libraries such as PyTorch/Fast.ai or TensorFlow/Keras. 
• Develop APIs and model architectures for computer vision, natural language processing or 3D deep learning applied to geospatial datasets. 
• Develop and pitch data science solutions by mapping business problems to machine learning or other advanced analytics approaches.
• Build high-quality analytics systems that solve our customers' business problems using techniques from data mining, statistics, and machine learning.
• Design, test, release, and support AI capabilities in the ArcGIS platform to enhance overall product quality and applicability for supporting data science and deep learning workflows with imagery. 
• Author and maintain geospatial data science samples using ArcGIS and machine learning/deep learning libraries. 
• Curate and pre/post-process data for deep learning models and transform it into geospatial information.
• Perform comparative studies of various deep learning model architectures. 
• Support internal teams in developing and pitching data science solutions by mapping business problems to machine learning or other advanced analytics approaches.
• Keep up to date with the latest technology trends in machine and deep learning and help position them in project delivery.
• Engage with our customers by discovering the value of location within customer workflows and driving substantial return on their investment in our system and services by creating outstanding proposals and winning work with strategic customers.
• Implement best practices and patterns for geospatial machine learning and develop reusable technical components for demonstrations and rapid prototyping.

Job Requirements

•  Degree in mathematics, statistics, computer science, physics, or a similar field 
•  2+ years of practical machine learning experience or applicable academic/lab work 
• Familiarity with one or more of the following: Git, Pytorch, Tensorflow, CUDA/GPU programming 
• Familiarity with ArcGIS suite of products and concepts of GIS 
• Knowledge of deep learning for natural language processing, probabilistic programming, and reinforcement learning 
• DevOps/MLOps experience using Docker/Kubernetes 
• Experience interacting with AWS, Azure, or other cloud service 
• Knowledge of remote sensing concepts and experience in handling geospatial datasets including satellite imagery, 3D point clouds/meshes, LiDAR, and other geospatial datasets 
• Experience in building and optimizing supervised and unsupervised machine learning models including deep learning and various other modern data science techniques 
• Experience with applied statistics concepts 
• Experience developing software collaboratively in Python using version control 
• Ability to perform data extraction, transformation, loading from multiple sources and sinks 

Additional Info