Artificial Intelligence Machine Learning Engineer - SE&IT

Lockheed Martin • Huntsville, AL

1d • Onsite

About The Position

Advancing the Integrated Discrimination and Electronic Protection capabilities of the Missile Defense System (MDS)
Leading systems engineering trades, analysis, and studies related to requirements generation
Developing and delivering MDS capabilities and engineering artifacts into the Technical Baseline (TBL) THE WORK The Systems Engineering and Integration Team is seeking an Artificial Intelligence Machine Learning Engineer to support the design, guidance, and implementation of AI/ML-enabled capabilities for missile defense mission areas. The successful candidate will contribute across multiple phases of the mission lifecycle, supporting analytical, modeling, simulation, and decision-support activities related to detection, tracking, discrimination, fi re control, and engagement functions within a complex system-of-systems environment.
The AI/ML Specialist will collaborate with systems engineers, domain experts, and software developers to identify appropriate problem formulations and opportunities for the application of AI/ML techniques. Responsibilities include developing and curating training and evaluation datasets from diverse sources, defining data management and labeling strategies, and designing scalable training, testing, and validation infrastructure consistent with program constraints and security requirements.
The candidate will be responsible for guiding the selection, development, and integration of AI/ML models into existing analytical, modeling, and simulation frameworks, ensuring alignment with system architectures, interfaces, and performance objectives. This includes supporting model evaluation, uncertainty characterization, robustness assessments, and lifecycle considerations such as retraining, configuration management, and traceability.
Artificial Intelligence Machine Learning Engineer will also contribute to the establishment of best practices, standards, and governance for AI/ML usage, including documentation, verification and validation approaches, and coordination with broader digital engineering and systems engineering processes. Emphasis will be placed on explain ability, testability, and integration within mission-relevant workflows, while maintaining compliance with applicable policies, security requirements, and program constraints.
The Artificial Intelligence Machine Learning Engineer will provide guidance and subject matter expertise to the Digital Ecosystem and Platforms team for the SE&I Team's AI adoption strategy. Key tasks include identification, evaluation, and integration of Large Language Model(s), as well as use case specific AI tooling such as SysML modeling and Integrated Development Environment (IDE) plug-ins.

Requirements

• Demonstrated experience applying multiple Artificial Intelligence and/or Machine Learning techniques (e.g., artificial neural networks, Bayesian belief networks, decision trees) to complex technical or analytical problems.
• Experience working with data-centric workflows, including data preparation, curation, labeling, and quality assessment for analytical or modeling purposes.
• Familiarity with the full AI/ML lifecycle, including model development, training, testing, validation, and iterative improvement.
• Experience collaborating with multidisciplinary teams, including systems engineering, software development, and domain subject matter experts.
• Ability to translate high-level mission or system objectives into well-defined analytical or computational problem statements.
• Experience documenting technical approaches, assumptions, and results in a clear and structured manner suitable for engineering and programmatic review.
• Understanding of basic software engineering practices, including version control, modular design, and reproducibility.
• Ability to work within established program constraints, including security, configuration management, and governance processes
• Experienced in systems engineering, particularly in requirements generation, concept development, analysis, and simulation
• Skilled in leading technical teams and providing oversight in a complex engineering environment
• Proficient in interfacing with technical stakeholders and managing technical documentation and baselines
• Adept at preparing and delivering technical briefings and engineering products
• Strong project management skills with experience in monitoring tasks, schedules, scope, and costs

Nice To Haves

• Experience applying AI/ML techniques within complex, distributed, or system-of-systems environments.
• Familiarity with modeling and simulation, digital engineering, or analytical frameworks used to support system design, assessment, or decision support.
• Experience with scalable training, testing, or evaluation infrastructure, including compute resource management and automation.
• Exposure to uncertainty quantification, robustness analysis, model verification and validation, or performance assessment methodologies.
• Experience supporting data governance, model traceability, or lifecycle management in regulated or mission-critical environments.
• Familiarity with explainable AI concepts or techniques and their application in engineering or decision-support contexts.
• Experience working in government, defense, aerospace, or other highly regulated technical domains.
• Ability to communicate technical concepts effectively to both technical and non-technical stakeholders.
• Experience supporting transition of analytical or AI/ML capabilities from development environments into operationally relevant workflows.
• Familiarity with hardware, programming languages, scientific computing environments, and resource management tools commonly used for data analysis and modeling to include graphical processing units (GPUs), Python / MATLAB / SQL, High Performance Computing (HPC) clusters and SLURM.

Responsibilities

• Developing and curating training and evaluation datasets from diverse sources
• Defining data management and labeling strategies
• Designing scalable training, testing, and validation infrastructure consistent with program constraints and security requirements
• Guiding the selection, development, and integration of AI/ML models into existing analytical, modeling, and simulation frameworks, ensuring alignment with system architectures, interfaces, and performance objectives
• Supporting model evaluation, uncertainty characterization, robustness assessments, and lifecycle considerations such as retraining, configuration management, and traceability
• Contributing to the establishment of best practices, standards, and governance for AI/ML usage, including documentation, verification and validation approaches, and coordination with broader digital engineering and systems engineering processes
• Providing guidance and subject matter expertise to the Digital Ecosystem and Platforms team for the SE&I Team's AI adoption strategy
• Identification, evaluation, and integration of Large Language Model(s), as well as use case specific AI tooling such as SysML modeling and Integrated Development Environment (IDE) plug-ins

Benefits

• Excellent benefits and amenities.
• Ongoing career development and support.
• Rewards and recognition for your hard work.
• Medical and dental coverage.
• 401k retirement savings plan.
• Paid time off for work/life balance.
• Mentorship opportunities
• Medical, Dental, Vision, Life Insurance, Short-Term Disability, Long-Term Disability, 401(k) match, Flexible Spending Accounts, EAP, Education Assistance, Parental Leave, Paid time off, and Holidays.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees