Job description

SAIC seeks an Artificial Intelligence/Machine Learning Systems Engineer to join our team of professionals providing technical and program services to the U.S. Government (USG). SAIC provides research, engineering, design, analysis, acquisition, development, integration, test, and operations support USG Intelligence Community (IC) and Department of Defense (DoD) customers. The AI/ML systems engineer sought here serves a USG Program Office leading Research & Development (R&D) of evolutionary, revolutionary, and transformational artificial intelligence and machine learning algorithms. This position provides Systems Engineering & Technical Advisory (SETA) support services. Job Description: • Work with government technical and contracts staff developing program acquisition packages including but not limited to statement of work, Justification & Approval, development of Request for Contract Action Package (RCAP) artifacts, Request For Information (RFI), Request For Proposal (RFP), and executive briefing materials • Provide acquisition advisory services during technical and cost evaluations of RFIs and/or proposals in support of source selection • Evaluation of advanced AI/ML concepts, systems, technologies, designs, architectures, interfaces into space and ground systems • Support Agile SAFe program development processes and activities such as Program Increment (PI) Planning, development of epics, features, and demo coordination • Assist USG Program Office with analysis of alternatives to optimize technical, cost, and schedule performance considerations and improve knowledge and understanding of system, technology, and architecture tradeoffs • Technical and programmatic support through the entire project life cycle including concept development, system definition, acquisition planning, source selection, system design, development, integration and test, system delivery, and deployment • Support systems engineering activities such as risk management, schedule management, and technical performance management • Briefings and reports including technical and programmatic assessments presenting analysis, results, conclusions, and recommendations • Assessment of white papers and vendor marketing materials Required Qualifications: • Active TS/SCI clearance with Poly • Assist in Interoffice and Interagency coordination and collaboration • Must have bachelor’s degree in science, technology, engineering, or math discipline with minimum of nine (9) years of relevant work experience or seven (7) years with master’s degree • Demonstrated acquisition support experience of 5 or more years • AI/ML experience • Proficient skills using Microsoft Office applications (i.e., Word, Excel, PowerPoint, SharePoint) • Proficient skills using Jira and Confluence tools • Critical thinking, problem-solving, and analytical skills • Interpersonal and communication skills for written reports, group discussion, and oral presentations Desired Qualifications: • Knowledge, skills, abilities, and/or experience in one of more of the following: • Systems engineering and integration applied to spacecraft, ground, and launch systems • R&D of artificial intelligence/machine learning agents • System acquisition, design, development, integration, test, and/or flight operations • Artificial Intelligence and/or Machine Learning technologies applied to space systems • IC mission, organizations, disciplines, systems, and/or processes • Experience working as a SETA • General understanding of satellite architecture (payloads and bus sub-systems) • General understanding of satellite operations (planning & scheduling, mission management, and command and control

Requirements

Must-haves

Provide acquisition advisory services during technical and cost evaluations of RFIs and/or proposals in support of source selection
Evaluation of advanced AI/ML concepts, systems, technologies, designs, architectures, interfaces into space and ground systems
Support Agile SAFe program development processes and activities such as Program Increment (PI) Planning, development of epics, features, and demo coordination
Assist USG Program Office with analysis of alternatives to optimize technical, cost, and schedule performance considerations and improve knowledge and understanding of system, technology, and architecture tradeoffs
Support systems engineering activities such as risk management, schedule management, and technical performance management
Briefings and reports including technical and programmatic assessments presenting analysis, results, conclusions, and recommendations
Assessment of white papers and vendor marketing materials
Active TS/SCI clearance with Poly
Assist in Interoffice and Interagency coordination and collaboration
Must have bachelor’s degree in science, technology, engineering, or math discipline with minimum of nine (9) years of relevant work experience or seven (7) years with master’s degree
Demonstrated acquisition support experience of 5 or more years
AI/ML experience
Proficient skills using Microsoft Office applications (i.e., Word, Excel, PowerPoint, SharePoint)
Proficient skills using Jira and Confluence tools
Critical thinking, problem-solving, and analytical skills
Interpersonal and communication skills for written reports, group discussion, and oral presentations

Nice-to-haves

Knowledge, skills, abilities, and/or experience in one of more of the following: • Systems engineering and integration applied to spacecraft, ground, and launch systems
R&D of artificial intelligence/machine learning agents
System acquisition, design, development, integration, test, and/or flight operations
Artificial Intelligence and/or Machine Learning technologies applied to space systems
IC mission, organizations, disciplines, systems, and/or processes
Experience working as a SETA
General understanding of satellite architecture (payloads and bus sub-systems)
General understanding of satellite operations (planning & scheduling, mission management, and command and control

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaimlagilejira

Platform: oracle-cloud
Effort: medium