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General Dynamics Information Technology•College Park, MD

20h•$111,155 - $150,385•Onsite

About The Position

The Data Scientist (AI/ML Engineer) designs, implements, and secures production machine-learning systems for classified intelligence missions. The position develops hardened ML architectures and microservices, implements containerized and clustered deployments, ensures compliance with RMF and OPSEC controls, optimizes models for constrained environments, and integrates AI/ML capabilities with mission systems and sensors. The role handles code and models securely, tunes performance, automates secure build and deployment pipelines, and coordinates with security and SSO personnel to prevent inadvertent disclosure during agile prototyping. It advances AI capabilities by designing and evaluating analytic methods, conducting independent research, and incorporating emerging technologies into all-source intelligence production, knowledge management, and analytic tradecraft. Work includes applying statistical methods, developing semantic automation workflows, improving knowledge-graph reasoning, enhancing entity extraction and summarization, and using ML for multi-INT analytic augmentation. The Data Scientist also supports tool and workflow modernization, scripts in R, Python, and SQL, manages disparate data sources, and evaluates AI/ML techniques for risks, biases, and limitations. The position contributes incremental capability enhancements, maintains familiarity with state-of-the-art technologies, and produces analytic outputs on emerging military technologies worldwide. The work supports all-source intelligence and scientific and technical intelligence for cyberspace operations, with the goal of enhancing defensive and offensive cyberspace operations. The position is onsite in College Park, Maryland, with 40 scheduled weekly hours and less than 10% travel required. A Top Secret SCI with Polygraph clearance is required, and U.S. citizenship is required.

Requirements

Top Secret SCI with Polygraph clearance must currently be possessed and must be maintainable/obtainable.
U.S. citizenship is required.
17 or more years of related experience is listed in the job qualifications.
A master's degree with 12 years of related experience or a bachelor's degree with 17 years of experience is required.
Professional or graduate-level certificate in data science from a recognized institution.
Experience with large-data multi-INT analytics, machine learning, and automated predictive analytics.
Skills listed include analytical thinking, datasets, and machine-learning methods.

Nice To Haves

Certified Kubernetes Administrator qualification.
Cloud GovCloud experience with AWS or Azure Gov.
RMF/security training.

Responsibilities

Design, implement, and secure production ML systems and deployments for classified environments, including hardened architectures, microservices, containerized and clustered deployments, RMF/OPSEC compliance, and mission-system integration.
Handle code and models securely, tune performance, automate secure CI/CD build and deployment pipelines, and coordinate with SSO and security personnel to prevent inadvertent disclosure during development.
Design, develop, and evaluate leading-edge AI technologies for integration into all-source analysis tradecraft, assessments, production workflows, dissemination, and knowledge management.
Propose and apply advanced statistical and mathematical techniques for model formulation, experimental design, and new analytic methodologies.
Collaborate on exploratory efforts using large language models, NLP, and ML to automate ontologies and support semantic accuracy and interoperability with knowledge-graph architectures.
Evaluate AI, data-science, and advanced analytic methods for risks, biases, and limitations that could distort analytic conclusions.
Develop and refine semantic data-retrieval and reasoning capabilities across knowledge graphs using GraphQL, SPARQL, SHACL, SQL, and other query frameworks.
Conduct independent research on analytic methods and technologies across government, industry, and academia, and inform senior leadership about their applicability to mission programs.
Investigate, prototype, and evaluate technologies that enhance all-source intelligence analysis.
Support automation of entity extraction, recognition, and summarization using ML/NLP techniques aligned with analytic tradecraft standards.
Research ways to augment or automate all-source analytic processes using computer-based models and AI/ML systems.
Deliver incremental enhancements to analytic tools, capabilities, workflows, and methods.
Write R or Python scripts, apply SQL, manage and merge disparate datasets, perform statistical analysis, and apply data-mining algorithms for mission analytics.
Use and maintain proficiency with TensorFlow/PyTorch, Docker, Kubernetes, CI/CD tools such as Jenkins/GitLab, GPU/HPC workflows, secure software-development practices, and model-optimization techniques.
Apply prior experience in large-data multi-INT analytics, ML, and automated predictive analytics.

Benefits

Comprehensive benefits and wellness packages.
401(k) with company match.
Competitive pay and paid time off.
Medical plan options, some with Health Savings Accounts.
Dental plan options.
Vision plan.
Full flex work weeks where possible.
Vacation, sick, and personal time off, plus holidays and paid parental, military, bereavement, and jury duty leave.
Short- and long-term disability benefits.
Life, accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance are provided or available.
Growth and learning opportunities through an AI-powered career tool.
Internal mobility support.