Principal Researcher for AI Risk Management

NIST is seeking an AI risk management expert to drive national leadership in trustworthy AI technology. This role involves maintaining NIST's AI Risk Management Framework (AI RMF), developing related ITL guidelines such as the AI RMF Playbook, and fostering community engagement to promote widespread AI RMF adoption and help others manage AI risk across sectors. This notice is issued under direct-hire authority to recruit new talent for occupations with a severe shortage of candidates.

Responsibilities

As an AI risk management expert, you will shape national and international practices for trustworthy AI technology via the NIST AI Risk Management Framework (AI RMF) and associated resources. Duties vary by grade level:

• ZP-IV Duties:
  • Promote AI RMF adoption to support trustworthy AI innovation and national technology leadership.
  • Develop guidelines, including the AI RMF Playbook, Quick Start Guide, context-specific profiles, and crosswalks.
  • Engage target communities to expand framework utilization and address evolving user needs.
• ZP-V Duties:
  • Serve as a national authority on the AI RMF across government and external sectors.
  • Define program strategy and long-term objectives for NIST's AI risk management portfolio.
  • Lead conception and creation of guidelines, e.g., for context-specific profiles.
  • Advise external agencies on effective framework implementation and build strategic user communities.
  • Brief agency leadership on AI governance trends and gaps related to the AI RMF.

Qualifications

Computer Scientist (ZP-1550)

Basic Requirements:

• Bachelor's degree in computer science or bachelor's degree with 30 semester hours in a combination of mathematics, statistics, and computer science. At least 15 of the 30 semester hours must have included any combination of statistics and mathematics that included differential and integral calculus.
• All academic degrees and coursework must be from accredited or pre-accredited institutions.

ZP-1550-IV: In addition to the basic requirements, applicants must have one year (52 weeks) of specialized experience at the GS-12 level (ZP-III at NIST), defined as:

• Experience conducting technical research or development work to study or implement artificial intelligence (AI) and machine learning (ML) tools.
• Experience drafting technical papers, guidelines, or standards intended to guide a broad community of AI/ML practitioners regarding best practices for applying AI/ML and managing AI/ML risk, either from a computational or behavioral and social sciences perspective.
• Experience serving as a technical representative or coordinator in multi-stakeholder or interagency technology-related fora, such as working groups or standards committees.

ZP-1550-V: In addition to the basic requirements, applicants must have one year (52 weeks) of specialized experience at the GS-14 level (ZP-IV at NIST), defined as:

• Experience conducting technical research or development work to study or implement artificial intelligence (AI) and machine learning (ML) tools.
• Experience formulating, leading, or managing complex computer science projects or technology policy initiatives of considerable scope and impact related to AI/ML.
• Experience developing and authoring technical papers, guidelines, or standards intended to guide a broad community of AI/ML practitioners regarding best practices for applying AI/ML and managing AI/ML risk, leveraging either computational or behavioral and social sciences perspectives.
• Experience leading collaborative work in multi-stakeholder or interagency technology-related fora, such as working groups or standards committees, to influence technology programs or technical consensus.

Social Scientist (ZP-0101)

Basic Requirements:

• Degree in behavioral or social science or related disciplines appropriate to the position.
• Or a combination of education and experience that provided knowledge of one or more of the behavioral or social sciences equivalent to a major in the field.
• Or four years of appropriate experience demonstrating knowledge of one or more of the behavioral or social sciences equivalent to a major in the field.

ZP-0101-IV: In addition to the basic requirements, applicants must have one year (52 weeks) of specialized experience at the GS-12 level (ZP-III at NIST), defined as:

• Experience conducting technical research or development work to study or implement artificial intelligence (AI) and machine learning (ML) tools.
• Experience drafting technical papers, guidelines, or standards intended to guide a broad community of AI/ML practitioners regarding best practices for applying AI/ML and managing AI/ML risk, either from a computational or behavioral and social sciences perspective.
• Experience serving as a technical representative or coordinator in multi-stakeholder or interagency technology-related fora, such as working groups or standards committees.

ZP-0101-V: In addition to the basic requirements, applicants must have one year (52 weeks) of specialized experience at the GS-14 level (ZP-IV at NIST), defined as:

• Experience conducting technical research or development work to study or implement artificial intelligence (AI) and machine learning (ML) tools.
• Experience formulating, leading, or managing complex computer science projects or technology policy initiatives of considerable scope and impact related to AI/ML.
• Experience developing and authoring technical papers, guidelines, or standards intended to guide a broad community of AI/ML practitioners regarding best practices for applying AI/ML and managing AI/ML risk, leveraging either computational or behavioral and social sciences perspectives.
• Experience leading collaborative work in multi-stakeholder or interagency technology-related fora, such as working groups or standards committees, to influence technology programs or technical consensus.

Experience includes paid and unpaid experience, including volunteer work through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional, philanthropic, religious, spiritual, community, student, social).