Systems Engineer - AI/ML Data Analysis

n \nGeneral Dynamics Mission Systems (GDMS) is seeking a motivated and technically skilled Senior Systems Engineer to join the Fleet Ballistic Missile (FBM) Sustainment team. In this role, you will serve as the primary owner of the Fleet Data Analysis System (FDAS) tool and will leverage cutting-edge Artificial Intelligence (AI) and machine learning techniques to develop scripts and automated workflows that analyze patrol data, identify trends, and support mission readiness decisions. This is a high-impact position supporting the United States Navy’s and Strategic Systems Programs (SSP) submarine-based strategic deterrent mission.\n \n, * Serve as the primary tool owner for the Fleet Data Analysis System (FDAS), managing configuration, maintenance, version control, and user support. \n

• Design, develop, and maintain AI-powered scripts and automated analysis tools to process and interpret submarine patrol data. \n

• Utilize Python, machine learning frameworks, and AI code-generation tools (e.g., GAIAA, GitHub Copilot) to accelerate data analysis workflows and reduce manual processing time. \n

• Analyze complex patrol datasets to identify anomalies, performance trends, and mission-critical insights for engineering and leadership review. \n

• Collaborate with systems engineers, data analysts, and program managers to define FDAS tool requirements and deliver continuous improvements. \n

• Support sustainment activities for FBM weapon system components, ensuring alignment with Navy specifications and GDMS engineering standards. \n

• Produce technical documentation, engineering reports, and briefings communicating findings derived from FDAS data analysis. \n

• Coordinate with Navy stakeholders and government customers to ensure FDAS outputs meet mission and reporting requirements. \n

• Identify opportunities to apply AI/ML innovations to improve patrol data processing efficiency, accuracy, and predictive maintenance capabilities. \n

• Maintain compliance with cybersecurity requirements, ITAR regulations, and program security protocols. \n

n \nBachelor’s degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 5 years of relevant experience; or Master’s degree, plus a minimum of 3 years of relevant experience.\n \n CLEARANCE REQUIREMENTS:\n Candidate must be able to obtain a DoD Secret security clearance within a reasonable amount of time to meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required.\n, * Bachelor’s degree in Systems Engineering, Electrical Engineering, Computer Engineering, Computer Science, or a related STEM field. \n

• 5 years of experience in systems engineering, data analysis, or related discipline. \n

• Demonstrated experience with data analysis tools and scripting languages (Python strongly preferred). \n

• Familiarity with AI/ML concepts and the ability to leverage AI-assisted tools (e.g., GAIAA, GitHub Copilot, ChatGPT) to create and maintain analysis scripts. \n

• Strong analytical and problem-solving skills with the ability to interpret complex technical data sets. \n

• Excellent written and verbal communication skills, including ability to produce engineering-quality reports and briefings. \n

• US Citizenship is required and candidate must be able to obtain a DoD Secret security clearance within a reasonable amount of time. \n

• Ability to work independently and collaboratively in a fast-paced sustainment environment. \n, * Familiarity with FDAS or similar Navy fleet data analysis systems and tools. \n

• Experience with ML libraries such as scikit-learn, TensorFlow, or PyTorch. \n

• Knowledge of data visualization tools (Tableau, Power BI, Matplotlib, Plotly). \n

• Experience with SQL databases and data pipeline development. \n

• Understanding of Navy systems engineering processes, MIL-STD specifications, and submarine lifecycle management. \n

• Experience working in an Agile or Scrum development environment. \n

• Familiarity with GDMS internal tools and the GAIAA AI assistant platform. \n