About the Company:
DigitalGlobe is a leading provider of commercial high-resolution earth observation and advanced geospatial solutions that help decision makers better understand our changing planet in order to save lives, resources and time. Sourced from the world's leading constellation, our imagery solutions deliver unmatched coverage and capacity to meet our customers' most demanding mission requirements. Each day customers in defense and intelligence, public safety, civil agencies, map making and analysis, environmental monitoring, oil and gas exploration, infrastructure management, navigation technology, and providers of location-based services depend on DigitalGlobe data, information, technology and expertise to gain actionable insight. DigitalGlobe is a public company listed on the NYSE as DGI, and is headquartered in Longmont, Colorado.
DigitalGlobe operates the largest and highest resolution commercial remote sensing satellite constellation and is building one of the largest image processing infrastructures in the world. Our latest satellite has 16 spectral bands and can identify material and mineral types, assess vegetation health, and even see through smoke to monitor wildfires.
We are looking for Research Scientists at Senior, Staff, and Principal levels to join our R&D team with focus on automated image exploitation. Strong candidates will have a comprehensive background in machine learning, computer vision, and image processing, along with experience in developing applications that execute efficiently in a large, distributed computing environment.
Development and implementation of algorithms for object recognition, change detection, and temporal monitoring.
Development of multi-modal feature extraction and advanced semantic models for image understanding.
Development of scalable solutions for image mining and data fusion.
Drive the R&D and productization of new geospatial data product layers.
Ph.D. in Computer Science, Electrical Engineering or a related discipline.
Expertise in the areas of Deep Learning and Domain Adaptation.
Experience with applying learning algorithms on large-scale data (hundreds of millions of train/test instances).
Ability to work independently as part of a geographically distributed team, self-motivated to produce results efficiently.
Solid software engineering skills in Java, Python, or C++. Familiarity with multithreaded and parallel programming in distributed cluster environments.
Experience with distributed processing (Hadoop, Spark, etc) on cloud based platforms such as AWS.
Knowledge of multi-spectral image processing, including VNIR and SWIR bands.
Familiarity with modern software engineering practices such as agile and continuous integration.
Experience with remote sensing and geospatial data products.
GPU (CUDA, OpenCL) experience is a plus.