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 Learing 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…