AI​/ML Engineer III

AI/ML Engineer III

The AI/ML Engineer III is a mid-level technical position that requires advanced expertise in designing, developing, and deploying machine learning systems for aerospace and defense applications. In this role, you will lead the creation of cutting-edge AI solutions for complex problems, such as autonomous navigation, sensor fusion, and real-time decision-making. You will also mentor junior engineers, manage key projects, and contribute to strategic decision-making within AI/ML development efforts.

Your work will directly impact mission-critical systems and next-generation technologies.

• Lead the design and development of advanced machine learning models, including deep neural networks, reinforcement learning systems, and generative AI algorithms, to solve complex problems.
• Architect scalable AI/ML systems that can integrate seamlessly with existing software and hardware platforms. Provide guidance on the selection of tools, frameworks, and infrastructure.
• Collaborate with systems engineers, hardware teams, and data scientists to align AI/ML solutions with mission-specific requirements and constraints.
• Manage AI/ML projects, including scoping, resource allocation, and timeline management, ensuring that deliverables meet quality and performance expectations.
• Develop and oversee robust validation and testing frameworks to ensure that AI/ML models meet performance, safety, and compliance standards in real-world scenarios.
• Mentor junior engineers, providing technical guidance and fostering a collaborative, innovative team environment.
• Stay current with emerging AI/ML technologies and propose innovative solutions to address new and existing challenges in the aerospace and defense domain.
• Communicate technical concepts, project progress, and outcomes to stakeholders, including leadership and external partners, in a clear and concise manner.
• Independently train, fine-tune, and optimize advanced AI architectures (including transformers) for complex applications.
• Apply a broad range of AI/ML techniques (supervised, unsupervised, reinforcement, generative) to solve domain-specific challenges.
• Lead the development and integration of signal processing, computer vision, and planning algorithms to advance autonomous system functionality.
• Design and execute large-scale simulations and modeling of AI/ML systems, ensuring scalability, performance, and robustness on CPU/GPU platforms.
• Lead rigorous validation and verification activities, ensuring deliverables meet performance, safety, and reliability requirements.

• Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
• 6+ years of experience in a related field.
• Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 9 years of related experience is required.
• Higher level relevant degree may substitute for experience.
• Proficient in machine learning frameworks (e.g., Tensor Flow, PyTorch) and skilled in implementing advanced AI/ML techniques, such as supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic), as well as working with generative AI models (e.g., transformers).
• Proficient in developing, deploying, and optimizing AI/ML models, including ANNs, CNNs, and RNNs, for production applications. Contributed to the design and scaling of systems for larger datasets or environments with moderate complexity.
• Strong proficiency in programming languages such as Python, C++, C# or Java, with experience in building scalable AI/ML systems.
• Demonstrated experience leading teams or projects, including mentoring junior staff.
• Proven track record of deploying AI/ML models in production environments and optimizing them for real-world use cases.
• Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications

• Master's degree in Artificial Intelligence, Machine Learning, or related field.
• Experience leading teams or projects in aerospace and defense industries.
• Familiarity with cybersecurity and regulatory requirements.
• Proficient in Agile or Dev Ops workflows; active participant in iterative ML software development.
• Practical experience designing and implementing advanced ML techniques, such as clustering, dimensionality reduction, or generative modeling.
• Hands-on experience with GPU programming and using high-performance computing systems for ML workloads.
• Experience with at least one reinforcement learning or generative AI model (e.g., implementing GANs or Transformers).
• Able to analyze large-scale, heterogeneous datasets and apply advanced statistical and ML methods to real-world problems.
• Experience translating mission objectives into actionable system requirements, including HMI scenarios.
• Familiarity with hardware acceleration (e.g., CUDA, TensorRT) and introductory knowledge of edge AI or XAI.