Artificial Intelligence & Machine Learning, Senior Advisor

**Position is Contingent Upon Award**

Join Peraton in advancing the safety, efficiency, and modernization of the National Airspace System (NAS) through the FAA’s Brand New Air Traffic Control System (BNATCS) contract. As a trusted partner to the Federal Aviation Administration, Peraton helps deliver the systems and services that keep our nation’s skies safe and connected.

We’re looking for innovative professionals who thrive in mission-critical environments and are passionate about shaping the future of air traffic management. This is your chance to make an impact on one of the world’s most vital transportation infrastructures, working alongside leaders in aviation, engineering, data science, and systems integration.

At Peraton, you won’t just support the mission — you’ll define it.

Join a team dedicated to protecting the safety and integrity of U.S. air travel. Peraton is seeking a AI/ML Research Scientist Senior Advisor to join our team of qualified, diverse individuals. The ideal candidate will influence national strategies and policies by guiding decisions on integrating next-generation technologies like Artificial Intelligence (AI), satellite navigation, and unmanned aircraft systems (UAS). Whether you’re supporting safety validation efforts or leading teams on major FAA programs, your work will directly impact the millions of passengers and aviation professionals who rely on safe, efficient airspace operations every day. The AI/ML Research Scientist Senior Advisor will work with senior research scientists and managers to perform research and development of AI/ML technologies such as natural language processing and generative AI.

In this position, you will:

• Provide guidance and strategic direction on research initiative to ensure they align with FAA requirements and program objectives
• Collaborate with leadership, research teams, and external partners to identify research opportunities, develop methodologies, advance innovations, and address complex scientific challenges.
• Collaborate with leading experts in government, academia, and industry to address some of the most complex challenges in modern aviation.
• Influence national strategies and policies by guiding decisions on integrating next-generation technologies like Artificial Intelligence (AI), satellite navigation, and unmanned aircraft systems (UAS).
• Contribute to critical research programs at premier facilities such as the William J. Hughes Technical Center, where cutting-edge simulations and testing shape the National Airspace System (NAS).
• Bridge research and operational application, ensuring innovative solutions are practical, safe, and ready for deployment across the aviation ecosystem.
• Conduct and guide research and development on technologies supporting the NAS, airport infrastructure, and air traffic management.
• Provide technical leadership and advisory support to FAA leadership on emerging technologies such as AI, satellite navigation, UAS, and advanced communications.
• Lead or contribute to design, testing, and innovation initiatives for next-generation aviation systems.
• Prepare technical reports, white papers, and presentations for FAA leadership and external advisory groups.
• Participate in special programs related to environmental and energy research.
• Oversee or support contractor-led research efforts to ensure alignment with FAA priorities and standards.

Why This Role Matters

The FAA is the cornerstone of aviation safety and innovation. As global air traffic grows and technology evolves, research scientists and advisors are essential to ensuring the United States remains at the forefront of aviation advancements. Your expertise will directly influence the safety of millions of passengers, improve operational efficiency, and guide the adoption of next-generation technologies. 

• U.S. Citizenship Required.
• Must have the ability to obtain / maintain a Public Trust clearance. 
• Bachelor’s degree and 12 years in Engineering, Computer Science, Physics, or a related technical field of experience or Masters degree and 10 years or PHD and 7 years experience. 
• Proven experience in research and development, data analysis, or specialized technical areas such as aerospace systems, AI, human factors, or wireless communications.
• Strong analytical, quantitative, and written communication skills, with the ability to translate complex concepts into actionable recommendations.
• Demonstrated expertise in one or more areas such as air traffic management systems, UAS integration, satellite navigation, environmental and energy research, or AI applications for aviation.
• Proven experience leading multi-disciplinary research teams or large-scale R&D projects.
• Hands-on experience with data analysis tools, modeling and simulation platforms, or advanced software development environments used in aviation research.
• Expertise in one or more programming languages: C. C++. Python
• AI/ML research experience, preferably with academic publications
• Hands-on development experience in AI/ML model building and tuning
• Experience in large language models
• Modern software development practices and toolsets (Git, CI/CD toolchains)

Preferred Qualifications:

• Exposure to FAA programs or NAS systems.
• Advanced degrees such as a master’s or Ph.D. strongly preferred.
• Advanced knowledge of aviation systems, UAS integration, AI applications, or satellite navigation systems.
• Experience participating in national advisory committees or providing strategic guidance for federal research programs.
• Familiarity with FAA research environments or facilities like the William J. Hughes Technical Center.
• Published research or recognized contributions to aerospace, human factors, or emerging aviation technologies.
• Familiarity with FAA regulations, national airspace policies, or international aviation standards (e.g., ICAO).
• Machine Learning libraries, such as TensorFlow, PyTorch, etc.
• NLP models and platforms, such as Llama2 and Hugging Face, etc.
• End-to-end machine learning model development experience
• Linux, containers such as Docker, and orchestration tool such as Kubernetes
• Cloud services experience (AWS, Azure)