AI-ML Modeling, Simulation and Analysis Engineer 112-124
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IC-CAP LLC is a Woman Owned / HUBZone Small Business working in the Department of Defense and Intelligence Community. We are always looking for highly talented, energetic, and dynamic professionals that are interested in protecting the defense of our nation.
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Some of the positions are future positions. Please look at the opening line of the job description to determine if this is an open or future position.
Our positions are not remote unless stated in the job description below.
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We are looking to fill this position at the following location(s):
- Chantilly, VA
Job Description
AI-ML Modeling, Simulation and Analysis Engineer will guide and conduct modeling, simulation, and analysis activities in support of business stakeholders, analysts, and warfighters to define and analyze system and data requirements to support NGA business and mission processes to ensure timely and accurate GEOINT. This position is focused on providing technical advisory support to identify capability gaps and needs, tools, technologies, and new agile methods and techniques ready to adapt to current innovations within Al R&D, particularly verification of Al models.
Responsibilities:
Performs Gap analysis and methodologies to identify the implications of artificial intelligence and machine learning for the future of warfare, and the specific defense and security applications (e.g., intelligence analysis, command and control, targeting, autonomous systems, information operations, training and simulation) where AI will be most impactful.
Assists in creating and leading Analysis of Alternatives (AoAs), Design of Experiments (DoE), Course of Actions (CoAs), Trade Studies, and Engineering Assessments.
Assists the Government in strategic technical planning, project management, performance engineering, risk management and interface design.
Assists with the planning, analysis/traceability of user requirements, architectures traceability, procedures, and problems to automate or improve existing systems and review cloud service capabilities, workflow, and scheduling limitations.
Experience in both quantitative and qualitative analysis to support sound metrics to uphold the confidence of the Al model assurance.
Assists Government in the creation of foundation of AI Assurance capabilities, including thorough formal methods for trusted and trustworthy eXplainable Al (XAI) and /or Independent Verification & Validation methodologies (IV&V) for AI (beyond T&E), T&EN&V-As-a-Service.
Work with leaders, scientists, and engineers across NGA, NSG, the (IC, ASG and US Government contractors for advancing, coordinating, and executing. corporate Al strategies and goals-particularly centered around Verified-AI (IV&V) and XAI.
Education and Experience
Required
DoD Approved Clearance and Poly
Master’s degree in computer science, Computer Vision, Artificial Intelligence, Machine Learning, or related STEM degree program, or equivalent Senior level experience as a MS&A Engineer.
12-18 years of experience.
Demonstrated experience in of Al Assurance, T&E or V&V-As-a-Service, and XAJ.
Demonstrated experience providing engineering solutions using Automation, Augmentation and Artificial Intelligence technologies.
Demonstrated experience using Test Driven Development leveraging computer programming languages to include but not limited to Python, C++, Matlab, R, Java.
Demonstrated experience of IV&V and the T&E status quo for AI models.
Desired
Demonstrated experience working with NGA Enterprise solutions to include Cl/CD pipeline and DevSecOps.
Demonstrated experience in SAFe framework and Model Based Systems Engineering.
Demonstrated experience in Atlassian products such as Confluence and JIRA.
Demonstrated experience with engineering solutions using Cloud-based technologies.
Demonstrated experience with engineering solutions using structured and unstructured Big Data.
Security Clearance:
Active TS/SCI and the willingness to sit for a polygraph, if needed
IC-CAP provides equal employment opportunities (EEO) to all applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status.