Job Description
Description
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:
- Lead 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
- 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
- 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
- Provide acquisition and programmatic expertise to support the planning of future systems and architectures, and oversight of development contractors
- Develop briefings and documentation material for Program / Project Manager’s engagements, including developing technical roadmaps and the acquisition strategies/documentation to implement them.
You will work side-by-side with the other LANDMARK AOS staff comprised of world class System Engineers, Acquisition Engineers and Domain Experts to lead the customer in acquiring modern processing applications.
Qualifications
TYPICAL EDUCATION AND EXPERIENCE: Bachelors and five (5) years or more experience; Masters and three (3) years or more experience; PhD and 0 years related experience
- Active Top Secret Clearance with Polygraph
- Strong engineering background with knowledge of software architectures and machine learning approaches for computer vision applications
- Demonstrated experience in managing technical, cost and schedule performance of software development programs
- Expertise and experience with the IC acquisition cycle, requirements processes, budgetary practices, and acquisition documentation
- Good working knowledge of MS Office applications
Desired Qualifications:
- Domain knowledge in Agile software development practices and Cloud computing architectures
- Experience supporting system architecture, design or development in an AWS/C2S environment
- Experience monitoring developer progress via agile metrics, identifying risks, discrepancies, and performance issues
- Certification in agile software development methods (Scrum, SAFe)
Overview
SAIC is a premier technology integrator solving our nation's modernization and readiness challenges. Our offerings across defense, space, civilian, and intelligence markets include high-end solutions in engineering, IT, and mission outcomes. We integrate the best components from our portfolio with our partner's ecosystem to deliver innovative and effective solutions. We are 25,500 strong; driven by mission, united by purpose, and inspired by opportunities. Headquartered in Reston, VA, SAIC has annual revenues of nearly $7.1 billion. For information, visit saic.com or Working at SAIC for benefits details. SAIC is an Equal Opportunity Employer empowering people no matter their race, color, religion, sex, gender identity, sexual orientation, national origin, disability, or veteran status. We strive to create a diverse, inclusive and respectful work culture that values all.
