Sr. Data Scientist – LOD3x Building Extraction, AI & Optimization

Overview

Passionate about 3D deep learning and 3D geometric processing research and solutions that will impact the work of hundreds of thousands of users? Join our AI Prototypes Team and push the frontiers of artificial intelligence working with point clouds, photogrammetric meshes, oriented imagery and elevation rasters to create new and exciting tools for 3D feature extraction. This is a great opportunity to join a research-oriented team that works with AI architectures and optimizations methods, publishes its research results and contributes to the development of the next generation Esri software.

Responsibilities

• Works on designing and prototyping practical pipelines for LOD3x (see Biljecki, F., Ledoux, H., Stoter, J. (2016): An improved LOD specification for 3D building models. Computers, Environment, and Urban Systems, vol. 59, pp. 25-37. for LOD specification) building extraction from photogrammetric meshes, gaussian splats, point clouds

• Creates datasets of LOD3x buildings, meshes, point clouds and gaussian splats for statistical evaluation of prototype and production code

• Designs and implements quantitative metrics for statistical evaluation of prototype and production code. Running leaderboards of various pipeline modifications, parameter values

• Works with stakeholders and developers on productization: Geoprocessing tool parameters, Python API, user and developer documentation

• Works with C++ developers on converting prototypes into production-grade implementations

• Designs and implements automated tests for production-grade implementations

• Presents the work at Esri user and developer conferences, third party venues

• Solves and articulates complex problems with design, development, and user experiences

• Additional R&D duties as assigned

Requirements

• 5+ years of experience in Python and Geoprocessing via ArcPy

• Experience with 3D in ArcGIS and 3rd party libraries: common data formats, visualization and analysis tools

• Knowledge of CGAL mesh solvers, fTetWild, Poisson mesh reconstruction, marching tetrahedra and cubes, and more

• Familiarity with ArcGIS stack: working with multi-band rasters, point clouds, multipatches, deep learning package

• Experience with optimization and Deep Learning

• Windows and Ubuntu experience

• Excellent written and verbal communication skills

• Bachelor's degree in computer or data science, mathematics, robotics, remote sensing, computer vision

Recommended Qualifications

• Familiarity with C/C++ coding

• Demonstrated experience with test automation

• Experience with scalable processing of large volumes of spatial data

• Knowledge of Pytorch3D or Kaolin

• Master's degree or Ph.D. in computer or data science, mathematics, robotics, remote sensing, computer vision

The Company

At Esri, diversity is more than just a word on a map. When employees of different experiences, perspectives, backgrounds, and cultures come together, we are more innovative and ultimately a better place to work. We believe in having a diverse workforce that is unified under our mission of creating positive global change. We understand that diversity, equity, and inclusion is not a destination but an ongoing process. We are committed to the continuation of learning, growing, and changing our workplace so every employee can contribute to their life’s best work. Our commitment to these principles extends to the global communities we serve by creating positive change with GIS technology. For more information on Esri’s Racial Equity and Social Justice initiatives, please visit our website here.

If you don’t meet all of the preferred qualifications for this position, we encourage you to still apply!

Esri is an equal opportunity employer (EOE) and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need reasonable accommodation for any part of the employment process, please email [email protected] and let us know the nature of your request and your contact information. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this e-mail address.

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