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    The Policy and Innovation Division supports aerospace innovation by creating novel means of compliance, develops and maintains Aircraft Certification Service regulations, manages the Aviation Safety (AVS) Senior Technical Experts Program (STEP) and overall fleet safety, as well as educational outreach. The Chief Scientific and Technical Advisor for Artificial Intelligence/Machine Learning is one of a cadre of nationally and internationally recognized technical experts comprising the AVS STEP.

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    The Chief Scientific and Technical Advisor (CSTA) for Artificial Intelligence/Machine Learning provides an FAA-wide, mission-critical, leadership role in identifying and mitigating aviation safety risk related to machine learning and artificial intelligence, and software development as it pertains to aerospace systems. The incumbent works to retain and broaden U.S. leadership related to how machine learning may be used in aviation systems, and how to evaluate integration of components based on machine learning with aircraft software. This may include specific areas such as algorithm development, data analysis, and analysis of neural net topologies, including techniques such as supervised and unsupervised machine learning algorithms, especially regression and convolution. The incumbent evaluates the readiness of emerging technologies, shapes agency policies, and promotes the adoption of safety enhancing operational requirements and practices into the FAA’s regulatory and certification programs. The CSTA also provides instruction and advice to the FAA, other departments and agencies, the aviation industry, professional societies, associations, academia, and international organizations.

    Specific responsibilities include:

    • Serves as a senior advisor in the Aviation Safety (AVS) Line of Business, providing scientific and engineering expertise and assistance to the relevant stakeholders working to enhance aviation safety, efficiency, and innovation. The incumbent provides expert advice and assistance to AVS managers and leaders, type certification boards, airworthiness directive boards, maintenance review boards, flight operation evaluation boards, special certification review teams, accident investigation teams, and special condition standards review activities.

    • Plans, directs, promotes, and coordinates research and the publication of scientific papers intended to evaluate new technologies, address service difficulties, and promote FAA adoption of the most safety enhancing policies and practices in the realm of machine learning.

    • Prepares and/or provides technical education and training to the FAA, industry, associations, foreign airworthiness certification authorities, and international organizations through certification projects, training courses, seminars, and workshops.

    • Represents the FAA in dealings with other civil aviation authorities, national and international forums, industry committees, and task groups on work to mitigate safety risk posed by machine learning. Coordinates regulatory initiatives with foreign airworthiness authorities to provide harmonized requirements and consensus standards in order to expedite and reduce the cost of international certification to the aerospace industry.

    • Supports industry and government in the investigation of accidents or incidents where machine learning or artificial intelligence are thought to have played a role. Collaborates with the National Transportation Safety Board and foreign entities by applying expertise in determining causal factors; identifying shortcomings in policy, technology, or practices; and recommending remedial actions to prevent or reduce the probability of such accidents or incidents in the future.

    Travel Required

    50% or less - The job may require up to 50% travel.

    Supervisory status


    Promotion Potential


  • Job family (Series)

    1550 Computer Science

This job originated on www.usajobs.gov. For the full announcement and to apply, visit www.usajobs.gov/GetJob/ViewDetails/610215000. Only resumes submitted according to the instructions on the job announcement listed at www.usajobs.gov will be considered.