Next-Gen AI/ML Systems Engineer - Data Fusion & Sense-Making

Peraton•Reston, VA

1d•Onsite

About The Position

Within Peraton's Space and Mission Solutions sector, there is an immediate need for a cleared AI (Artificial Intelligence) Data Fusion & Sense-Making emergent technologist to advance our artificial intelligence and data analytics capabilities across the US Intelligence and Space Community portfolio. This is a full-time, on-site position based in Reston, VA with the ability to support from other Peraton facilities in Chantilly, Reston, and/or Herndon with flexibility to travel to customer sites for classified and non-classified solution activities. As a Next-Gen Technology Engineer (NTE), reporting directly to the Sector CTO, you will be the organization's expert on leveraging artificial intelligence to transform disparate data sources into actionable intelligence. You will bring a broad, strategic view of AI applications, understanding not just what AI can do, but where and how it should be applied to maximize mission impact. Your expertise in AI testing, validation, and responsible AI practices will ensure our solutions are trustworthy and operationally effective. This role is designed for professionals who combine deep AI/ML (Artificial Intelligence/Machine Learning) technical skills with practical defense sector experience. You understand that AI adoption in government requires more than technical excellence—it demands rigorous testing, explainability, and alignment with customer missions and constraints.

Requirements

A minimum of 5+ years of experience with a BS/BA in Computer Science, Data Science, Mathematics, or related field; or 3+ years with MS/MA in Computer Science, Data Science, Mathematics, or related field; or 1+ PhD with relevant AI/ML research.
This position requires the candidate to possess a minimum of Secret clearance with the ability to obtain TS/SCI. The candidate must maintain the clearance.
Demonstrated expertise in AI/ML techniques for data fusion, integration, or analytics—including experience with multiple data modalities
Hands-on experience with AI testing, validation, and evaluation methodologies
Broad understanding of AI landscape including supervised/unsupervised learning, deep learning, NLP, computer vision, and foundation models
Working knowledge of data management practices, data pipelines, and data quality considerations for AI systems
Exposure to defense or intelligence community environments and understanding of unique AI adoption challenges in classified settings
Strong written and verbal communication skills with ability to explain AI concepts and limitations to non-technical audiences
Pragmatic approach to AI—understanding that not all problems require AI solutions and that customer readiness varies significantly
Full-time on-site availability with ability to collaborate across technical, business development, and program teams

Nice To Haves

An active/current TS/SCI is highly desired
Direct experience supporting NRO, NGA, USSF, DIA, NASA, or NOAA missions and programs
Knowledge of responsible AI frameworks, AI ethics, and bias mitigation techniques
Familiarity with MLOps practices, model monitoring, and AI system lifecycle management
Experience with AI development platforms and frameworks (PyTorch, TensorFlow, Hugging Face, etc.)
Relevant certifications or credentials in AI/ML, data science, or analytics
Experience contributing to proposals with AI/ML technical components
Graduate coursework or research publications in AI/ML, data fusion, or related fields

Responsibilities

Lead the design of AI-enabled data fusion solutions that integrate multi-source intelligence (SIGINT, GEOINT, HUMINT, OSINT, etc) into coherent, actionable insights for government proposals
Develop AI/ML architectures for data management, optimization, and sense-making that address customer-specific mission requirements
Establish and apply AI testing and validation frameworks to ensure solution reliability, explainability, and compliance with responsible AI principles
Maintain broad awareness of AI landscape—from foundation models to specialized ML techniques—and translate capabilities into practical mission applications
Create AI adoption roadmaps that account for customer readiness, data maturity, and organizational change management requirements
Collaborate with business development, capture teams, and program managers to identify AI opportunities and develop differentiated technical solutions
Infuse existing programs with AI capabilities where appropriate, working within operational and security constraints to demonstrate value incrementally
Mentor, train, and/or educate technical staff on AI/ML fundamentals, testing practices, and application strategies, building organizational AI literacy
Articulate AI solutions, their limitations, and mission impact to senior leadership, customers, and governance review boards