AI/ML Engineer III

About the role

The AI/ML Engineer III is a mid‑level technical role focused on designing, developing, and deploying advanced machine learning systems for aerospace and defense applications, leading AI solutions, managing projects, and mentoring junior engineers.

About the company

SNC is a global leader in aerospace and national security, delivering leading‑edge technologies and transformative solutions to support critical security needs and advance the American Dream.

Requirements

• Bachelor’s degree in computer science, mathematics, applied statistics, engineering or related STEM discipline (or 9 years related experience if no degree)
• 6+ years of relevant experience (or 9 years if no degree)
• Proficient with machine learning frameworks such as TensorFlow or PyTorch and advanced techniques including supervised, unsupervised, reinforcement learning (e.g., PPO, Actor/Critic) and generative AI models (e.g., transformers)
• Experience developing, deploying, and optimizing AI/ML models (ANNs, CNNs, RNNs) for production applications
• Strong programming skills in Python, C++, C# or Java and building scalable AI/ML systems
• Demonstrated experience leading teams or projects and mentoring junior staff
• Proven track record deploying AI/ML models in production and optimizing for real‑world use cases
• Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense
• Master’s degree in AI, ML or related field (preferred)
• Experience leading teams or projects in aerospace and defense industries (preferred)
• Familiarity with cybersecurity and regulatory requirements (preferred)
• Proficiency in Agile or DevOps workflows for iterative ML software development (preferred)
• Practical experience with advanced ML techniques such as clustering, dimensionality reduction, or generative modeling (preferred)
• Hands‑on experience with GPU programming and high‑performance computing for ML workloads (preferred)
• Experience with at least one reinforcement learning or generative AI model (e.g., GANs, Transformers) (preferred)
• Ability to analyze large‑scale heterogeneous datasets and apply advanced statistical and ML methods (preferred)
• Experience translating mission objectives into actionable system requirements, including HMI scenarios (preferred)
• Familiarity with hardware acceleration (CUDA, TensorRT) and introductory knowledge of edge AI or XAI (preferred)
• Ability to lead and manage complex AI/ML projects
• Willingness to travel up to 10‑20% to testing sites, customer locations, or conferences
• Comfort working in a hybrid environment managing cross‑functional teams