Spatiotemporal Data Researcher
Job location: Bethesda, MD
The technical SME develops software algorithms capable of autonomously associating (re-identifying) all instances of the same subject (primarily people and vehicles, with extension to generic objects during the program) across all video footage in a collection: across space, across time and across differing video sensor types and collection geometries.
The following are required qualifications:
Bachelors' degree in physics, mathematics, computer science, or relevant engineering fields (e.g. electrical, computer, systems, software) with eight plus (8+) years of work experience, or Masters' degree with four plus (4+) years of work experience, or PhD with two plus (2+) years of work experience. PhD is desirable , but not absolutely required if work experience provides depth and breadth of technical understanding and evidence of problem-solving capability equivalent to what would be expected for a PhD.
Five (5) years of experience in computer vision R&D
Two (2) years of experience with R&D of machine learning and deep learning algorithms
One (1) year of experience managing a multi-disciplinary research and development (R&D) or Test and Evaluation (T&E) team
Two (2) years of experience creating program plans, work breakdown structures, and milestone schedules
Excellent writing and editing skills. Ability to develop succinct, comprehensive, understandable documents using complex data from multiple sources.
Excellent slide development and PowerPoint skills. Ability to visually communicate complex ideas at a high level for technically savvy, but non-expert audiences.
Strong organizational, problem solving, and time management skills. Must be detail oriented.
Ability to proactively manage multiple, concurrent tasks
Experience in the Intelligence Community (IC) or Department of Defense (DoD), including experience with requirements, CONOPS and research technology transition
Objective (Desired) Expertise
The following are relevant and strongly desired qualifications: Experience with architectures to support large spatiotemporal data management and processing
Experience with the institutional review board (IRB) process for human subjects' research and IRB approved video collection
Experience with development in the Open Media Processing Framework (OpenMPF)
Experience with deployment of computer vision analytics in a large-scale framework
Experience managing/performing large-scale video collection, curation and annotation
Experience with video collection from fixed security/surveillance, airborne (e.g. drone, UAV), and ground mobile (e.g. cell phone, auto mounted, etc.) video sensors
Experience with image or video frame geo-localization
TENICA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
