Sabre Systems is seeking an AI/ML Engineer & Data Management Specialist (Journeyman) to support the Combat Survivability Division’s Low Observables (LO) Life Cycle Management (LCM) mission at NAS Patuxent River in Lexington Park, MD. This role combines advanced data science, artificial intelligence, machine learning, and comprehensive data management responsibilities to strengthen LO sustainment performance across multi-level security environments. This is an in-person on-site position at NAS Patuxent River and is not eligible for telework. Anticipated Travel requirements are less than 10%. 

The selected candidate will be responsible for but not limited to:

• Effectively and efficiently operate and communicate across multi-level security environments.
• Coordinate, gather, clean, and integrate technical and programmatic data from multiple program and project offices.
• Work closely with data management specialists to structure, maintain, and ensure the integrity of large, complex, multi-source datasets.
• Apply artificial intelligence and machine learning models (e.g., CAPRA, GenAI) to support gap analyses, business case analyses, and readiness assessments.
• Develop and refine prompts to optimize the performance and relevance of AI‑generated outputs for project needs.
• Build, validate, and interpret predictive models to assess LO sustainment performance, forecast readiness trends, and identify capability or resource gaps.
• Manage, maintain, and optimize relational and/or non-relational databases to ensure data availability, reliability, and performance.
• Design, implement, and manage Extract-Transform-Load (ETL) processes, validation routines, and data quality checks to maintain high data integrity.
• Create clear, concise data visualizations, summaries, and technical reports to communicate findings to engineers, logisticians, and leadership.
• Ensure all data management and analysis activities comply with DoD/NAVAIR security, privacy, and regulatory requirements, including access controls and audit trails.

Minimum Qualifications

• Accredited BA or BS degree relevant to data science, analytics, data management, or information technology.
• At least three (3) years of recent and relevant experience in data science, analytics, or data management.
• Demonstrated experience delivering results in multi-level security environments.
• Experience in data analysis, predictive modeling, or applied statistics in a technical or programmatic setting.
• Hands-on experience utilizing artificial intelligence and machine learning models, including prompt engineering for GenAI or similar tools.
• Ability to organize, clean, and maintain large, multi-source datasets and ensure high data integrity.
• Proficiency in data integration and Extract-Transform-Load (ETL) processes, including data migration between systems.
• Ability to create clear, concise, and actionable data visualizations using tools such as Tableau, Power BI, or similar tools.
• Familiarity with data security, privacy, and compliance requirements in DoD or government environments.
• Strong interpersonal and communication skills for working with multi-disciplinary teams, including engineers, logisticians, program managers, and data specialists.
• Clearance: Active TS with SAP eligibility required; SCI eligibility desired; optimal qualifications include existing C-Net access and SCI Access Indoctrination; Must be a U.S. Citizen

Desired Qualifications

• Direct experience supporting ACAT‑level programs.
• Advanced degree in a relevant discipline.
• Direct experience working with defense, aerospace, or government technical/programmatic data.
• Experience with Python, R, SQL, or similar languages for data manipulation and analysis.
• Experience automating data workflows or data management tasks using scripting languages or workflow automation tools.
• Demonstrated experience managing and maintaining large datasets in technical or programmatic environments.
• Experience developing and implementing data quality assurance or auditing processes.
• Ability to create and maintain metadata repositories, data dictionaries, and documentation to support data transparency and usability.

#LI-CS3

• A Level 3 Employee Referral Bonus applies to this requisition for qualifying referrals. At Sabre Systems, we value great talent and encourage our employees to refer exceptional candidates. If you have any questions about the referral policy or this position, please contact the Recruiting team.

Sabre Systems, LLC, has been providing innovative technological solutions and services for Department of Defense, Federal Civilian, and commercial customers for more than 35 years. We support the ever-evolving areas of advanced communication technologies, cyber, systems and software engineering, and digital transformation.  

With over three decades in business, Sabre Systems, LLC remains committed to our small business values and a people-first philosophy. We foster a welcoming, inclusive culture that values diverse perspectives and encourages open communication. Our collaborative environment supports continuous learning and professional growth at all levels. We prioritize the health, well-being, and success of our employees, offering comprehensive, evolving benefits designed to meet their diverse needs. Join us and be part of a thriving, people-driven culture.

We respect the unique perspectives that a diverse workforce of minorities, women, individuals with disabilities, and protected veterans brings not only to our company, but also to our customers. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity and sexual orientation), national origin, age, disability or genetic information.

EEO Minorities/Females/Disability/Veterans; VEVRAA Federal Contractor

Beware of employment scams-Sabre Systems will never request payment, extend offers without an interview, or contact you from an email that doesn’t end in @sabresystems.com; always apply directly at https://careers.sabresystems.com/. 

Sabre Systems is seeking an AI/ML Engineer & Data Management Specialist (Journeyman) to support the Combat Survivability Division’s Low Observables (LO) Life Cycle Management (LCM) mission at NAS Patuxent River in Lexington Park, MD. This role combines advanced data science, artificial intelligence, machine learning, and comprehensive data management responsibilities to strengthen LO sustainment performance across multi-level security environments. This is an in-person on-site position at NAS Patuxent River and is not eligible for telework. Anticipated Travel requirements are less than 10%. 

The selected candidate will be responsible for but not limited to:

• Effectively and efficiently operate and communicate across multi-level security environments.
• Coordinate, gather, clean, and integrate technical and programmatic data from multiple program and project offices.
• Work closely with data management specialists to structure, maintain, and ensure the integrity of large, complex, multi-source datasets.
• Apply artificial intelligence and machine learning models (e.g., CAPRA, GenAI) to support gap analyses, business case analyses, and readiness assessments.
• Develop and refine prompts to optimize the performance and relevance of AI‑generated outputs for project needs.
• Build, validate, and interpret predictive models to assess LO sustainment performance, forecast readiness trends, and identify capability or resource gaps.
• Manage, maintain, and optimize relational and/or non-relational databases to ensure data availability, reliability, and performance.
• Design, implement, and manage Extract-Transform-Load (ETL) processes, validation routines, and data quality checks to maintain high data integrity.
• Create clear, concise data visualizations, summaries, and technical reports to communicate findings to engineers, logisticians, and leadership.
• Ensure all data management and analysis activities comply with DoD/NAVAIR security, privacy, and regulatory requirements, including access controls and audit trails.

Minimum Qualifications

• Accredited BA or BS degree relevant to data science, analytics, data management, or information technology.
• At least three (3) years of recent and relevant experience in data science, analytics, or data management.
• Demonstrated experience delivering results in multi-level security environments.
• Experience in data analysis, predictive modeling, or applied statistics in a technical or programmatic setting.
• Hands-on experience utilizing artificial intelligence and machine learning models, including prompt engineering for GenAI or similar tools.
• Ability to organize, clean, and maintain large, multi-source datasets and ensure high data integrity.
• Proficiency in data integration and Extract-Transform-Load (ETL) processes, including data migration between systems.
• Ability to create clear, concise, and actionable data visualizations using tools such as Tableau, Power BI, or similar tools.
• Familiarity with data security, privacy, and compliance requirements in DoD or government environments.
• Strong interpersonal and communication skills for working with multi-disciplinary teams, including engineers, logisticians, program managers, and data specialists.
• Clearance: Active TS with SAP eligibility required; SCI eligibility desired; optimal qualifications include existing C-Net access and SCI Access Indoctrination; Must be a U.S. Citizen

Desired Qualifications

• Direct experience supporting ACAT‑level programs.
• Advanced degree in a relevant discipline.
• Direct experience working with defense, aerospace, or government technical/programmatic data.
• Experience with Python, R, SQL, or similar languages for data manipulation and analysis.
• Experience automating data workflows or data management tasks using scripting languages or workflow automation tools.
• Demonstrated experience managing and maintaining large datasets in technical or programmatic environments.
• Experience developing and implementing data quality assurance or auditing processes.
• Ability to create and maintain metadata repositories, data dictionaries, and documentation to support data transparency and usability.

#LI-CS3