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  • US Citizen only 
  • Salary range is $ 39k to $ 93k depending on your experience.

  • Apply expertise to develop new concepts, methods, and technologies, formulate plans, and conduct research and experimentation in geostatistical-analysis, analysis and development of computational systems and the development of computer based models.
  • Discuss project goals, equipment requirements, or methodologies with colleagues or team members.
  • Attend meetings or seminars or read current literature to maintain knowledge of developments in the field of remote sensing.
  • Review professional literature to maintain professional knowledge.
  • Attend conferences or workshops to maintain professional knowledge
  • Prepare or deliver reports or presentations of geospatial project information.
  • Prepare scientific or technical reports or presentations.
  • Experienced with implementing use-cases for prototype technology
  • Ability to design and complete research and development project
  • The individual must have one to four years of experience in one or more of the expertise in remote sensing, programming, software architect, machine and deep learning, and lidar.

  • Programing
  • Python, and ideally desired IDL and R
  • Developing ESRI ArcMap/ArcGIS Pro tools, particularly Python Toolboxes
  • ESRI (ArcMap, Pro) software product design, maturation and testing (finished products)
  • Robot Operating System (ROS) / Gazebo / Rviz / Rtabmap / C / C++

  • Lidar
  • Advanced experience with 3D point cloud acquisition and processing from both lidar and passive point clouds
  • Advanced GPS data processing for autonomous navigation
  • Unmanned Aerial System operation (including FAA training certifications)
  • Integration of emerging sensors for localization, object Detection, autonomy

  • Remote Sensing
  • Analyze data acquired from aircraft, satellites, or ground-based platforms, using statistical analysis software, image analysis software, or Geographic Information Systems (GIS).
  • Analyze geographical data.
  • Process aerial or satellite imagery to create products such as land cover maps
  • Conduct research into the application or enhancement of remote sensing technology.
  • Evaluate new technologies or methods
  • Participate in field work
  • Develop new analytical techniques or sensor systems
  • Develop automated routines to correct for the presence of image distorting artifacts, such as ground vegetation
  • Develop software or applications for scientific or technical use
  • Proficient in digital image processing for remotely sensed data
  • Proficient in one or more sensor modalities (Multispectral, LiDAR, SAR)
  • Design and implementation of fundamental experimentation focusing on:
  •       multi-modal active and passive sensing systems
  •       advanced computational analyses, using spatial-temporal big data sets
  •       basic earth system processes modeling to investigate interactions between air, water, soil, and built up environments
  • Familiarity with machine learning, particularly with deep learning and applications in remote sensing data
  • Implement artificial intelligence and machine learning methods in geospatial applications
  • Knowledge of supervised techniques for regression and classification; unsupervised techniques for statistical analysis; methods for pattern identification and prediction; image processing and feature extraction; probabilistic decision models; general knowledge of clustering, neural networks, tensors, and related AI techniques.    

  • Software Architect duties/responsibilities
  • Design, develop and execute software solutions to address geospatial challenge problem areas
  • Provide SW guidance and technical leadership to IT team members
  • Evaluate and recommend tools, technologies and processes to ensure the highest quality end-products
  • Collaborate with peer organizations and end users to produce cutting-edge software solutions
  • Interpret mission requirements to address the business application needs of the organization   
  • Troubleshoot and debug code level problems quickly and efficiently