AI Machine Learning Engineer

AI Machine Learning Engineer

Full-Time | On-Site or Hybrid (No Remote)

• Location:
  
  Huntsville, AL;
  Foothill Ranch, CA;
  Arlington, VA;
  Colorado Springs, CO
• Citizenship:
  United States citizenship required
• Security Clearance:
  An existing Secret security clearance is a preferred but not required; all offers are contingent upon the ability to obtain and maintain a U.S. government security clearance

Exo Analytic Solutions is a defense technology company developing cutting-edge sensor signal processing, algorithms, modeling, simulation, and analytics tools to support mission-critical defense and space systems. Our software and sensor technologies enhance the missile and space defense domains and enable faster, data-driven decision-making for national defense.

As an employee-owned company, we combine deep technical expertise with a culture of innovation, autonomy, and shared success. Our engineers work at solving problems of global importance.

Exo Analytic Solutions develops advanced algorithms, AI/ML solutions, and software tools for modeling, simulation, sensing, and decision support across space and missile defense systems. We are a recognized leader in algorithm development and applied artificial intelligence, delivering technically rigorous solutions to problems of national importance.

Exo Analytic Solutions is seeking an AI Machine Learning Engineer – Space & Missile Defense to join a multidisciplinary team developing advanced machine learning–driven capabilities for sensing, tracking, decision-making, and battle management. This role focuses on the design, development, integration, and evaluation of AI/ML algorithms within modeling, simulation, and operational decision-support environments. The ideal candidate is comfortable working at the intersection of AI/ML, algorithms, and complex physical systems, and enjoys translating operational challenges into deployable AI-enabled solutions.

This position is well suited for engineers who want to apply modern AI/ML techniques—such as deep learning, reinforcement learning, probabilistic reasoning, and multi-agent systems—to real-world aerospace and defense problems, while collaborating closely with systems engineers, analysts, and domain experts.

• Design, develop, and evaluate AI/ML algorithms for space and missile defense applications, including sensing, tracking, classification, prediction, and decision-making
• Implement machine learning solutions within modeling and simulation environments, analytical tools, and prototype operational systems
• Develop and train models using supervised, unsupervised, and reinforcement learning techniques
• Integrate AI/ML components with physics-based models, simulations, and system-level architectures
• Analyze AI/ML performance, limitations, uncertainty, and robustness in operationally relevant scenarios
• Collaborate with systems engineers, analysts, and domain experts to translate mission needs into AI/ML-driven solutions
• Support experimentation, test campaigns, and algorithm trade studies using simulated and real-world data
• Document algorithms, assumptions, data requirements, and performance results for technical and non-technical stakeholders
• Contribute to technical planning, architecture decisions, and proposal development as needed
• Manage individual tasks and deliverables while contributing to team-level technical decision-making

• Strong foundation in machine learning and artificial intelligence concepts, including model development, training, validation, and evaluation
• Proficiency in Python for AI/ML development; experience with C++ or similar languages is a plus
• Experience with modern ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar)
• Demonstrated experience developing, implementing, or integrating AI/ML algorithms into software systems or simulations
• Understanding of data preprocessing, feature engineering, model evaluation, and performance metrics
• Experience using version control systems (e.g., Git) in a collaborative development environment
• Ability to reason about algorithm tradeoffs, assumptions, uncertainty, and failure modes
• Ability to…