Job ID: 2208225Location: CHANTILLY , VA , US Date Posted: 2022-06-01Category: Engineering and SciencesSubcategory: Systems EngineerSchedule: Full-timeShift: Day JobTravel: NoMinimum Clearance Required: TS/SCI with PolyClearance Level Must Be Able to Obtain: NonePotential for Remote Work: NoDescription SAIC is seeking a Computer Vision Systems Engineer to fill a critical position on the LANDMARK AOS program. The position will be located in Chantilly, VA. All candidates must have an active TS/SCI clearance with Polygraph. LANDMARK AOS is a large SETA contract, supporting the customer's Ground Enterprise Directorate (GED), responsible for the acquisition of systems over the complete end-to-end life cycle. This position will provide specialized engineering expertise supporting the acquisition of computer vision (machine learning automated target recognition) software services. SAIC's client is tasked with leading the integration of mission focused tools to foster increased efficiency, automation and information sharing. The qualified candidate will assist and advise Government managers responsible for the complete end-to-end life cycle of the customer's Ground Enterprise. Job Responsibilities:
- Provide program management and technical engineering support to the Government customer to manage computer vision machine learning analytics programs; execute and evaluate cost, performance, schedule and risks throughout the program life-cycle
- Provide acquisition and programmatic expertise to support the planning of future systems and architectures, and oversight of development contractors
- Apply systems analysis and design methodology assessments to identify technical debt, architectural runway and efficiency trade-offs against current and proposed/desired cloud-based software system design
- Develop briefings and documentation material to illustrate features, capabilities and mission use cases for the computer vision tool portfolio, including developing technical roadmaps and the acquisition strategies/documentation to implement them.
- Facilitate technical and programmatic interchanges; identify and resolve issues; and provide engineering and technical advice to the customer to achieve innovative capabilities for automated machine learning analytics