LEAD ANALYST - LEAD ENGINEER - PRINCIPAL ENGINEER - AI & Machine Learning Intelligent Avionics

Who We Are: The Strategic Aerospace Department in the Defense & Intelligence Solutions Division provides the USAF with engineering services that increases the warfighters capabilities specifically for the bombers, tankers and heavies platforms.

Check out the role overview below If you are confident you have got the right skills and experience, apply today.

Objectives of this Role: Lead advanced AI/machine learning (ML) research and development for aerospace mission systems, embedded avionics, intelligent sensing, autonomy, and real-time edge computing across the Department's strategic avionics portfolio.

Develop physics-informed and data-driven ML approaches for sensor fusion, system identification, anomaly detection, prediction, decision support, and adaptive mission-system capabilities.

Architect, prototype, and transition AI/ML algorithms from research environments into deployable embedded hardware using C/C++, Python, heterogeneous processors, and real-time software frameworks.

Provide senior technical leadership for multidisciplinary integration of AI-enabled hardware/software into complex avionics systems, including laboratory, SIL/HIL, subsystem, and platform-level verification.

Advance Department AI capabilities through technical strategy, customer engagement, proposals, publications, technology demonstrations, mentoring, and transition of research into funded aerospace programs.

Daily and Monthly Responsibilities: Design, implement, optimize, and validate AI/ML algorithms for embedded aerospace and avionics applications, including physics-informed ML, sensor fusion, inference, prediction, classification, and autonomy.

Develop production-quality Python and C/C++ software and deploy trained models to real-time embedded compute platforms; profile latency, memory, power, determinism, reliability, and mission performance.

Integrate AI algorithms with avionics hardware, sensors, communications, mission software, and test assets; develop and execute SIL/HIL experiments, data pipelines, verification methods, and performance assessments.

Collaborate with electrical, embedded software, systems, RF, mechanical, test, cybersecurity, and flight-domain engineers to solve complex AI integration, interface, timing, assurance, and qualification challenges.

Lead technical reviews, trade studies, experiments, customer demonstrations, proposals, white papers, and technical reports; mentor engineers and establish reusable AI/ML architectures, tools, and engineering practices.

Requirements: Requires a Bachelors or a Masters degree in Electrical Engineering, Computer Engineering, Aerospace Engineering, Engineering Physics, Applied Mathematics, Data Science, or related engineering or technical degree field.

Graduate degrees in AI or Machine Learning or a closely related discipline are strongly preferred.

12+ years: Progressive engineering experience developing advanced AI/ML, data science, intelligent systems, or autonomy solutions, with demonstrated technical leadership and successful transition of algorithms into operational hardware/software.

12+ years: Proven expertise in physics-informed machine learning, scientific ML, system identification, reduced-order modeling, estimation, optimization, uncertainty quantification, or hybrid physics/data-driven methods.

12+ years: Expert-level Python and C/C++ development with hands-on experience using modern ML frameworks such as PyTorch, TensorFlow, JAX, or equivalent, and deploying models to embedded CPU/GPU/FPGA or other edge-compute hardware.

12+ years: Demonstrated aerospace/defense avionics experience integrating AI-enabled capabilities with sensors, mission systems, embedded electronics, real-time interfaces, SIL/HIL test environments, and verification/validation processes. xhyhwjd

A valid/clear driver's license is required.