Member of Technical Staff, Frontier Assessment

Summary

CAISI is a center of AI expertise in the U.S. government. Its Frontier Assessment team is hiring a Member of Technical Staff to develop novel means of evaluating AI, track strategic competition and threats to national security, assess economically important capabilities, produce briefings, build technical infrastructure, and track AI diffusion. This notice is issued under direct-hire authority to recruit new talent to occupations for which NIST has a severe shortage of candidates.

• You will drive technical projects from problem definition through delivery, producing excellent work at a rapid pace.
• Work independently as a technical contributor or lead a team, set technical direction, and coordinate work across projects.
• Develop, adapt, or execute evaluations of U.S. and foreign AI systems to inform understanding of capability levels, international AI competition, including agent-based performance in domains relevant to national security.
• Conduct research and analysis on the state of AI, including tracking AI progress indicators, analyzing development trends, executing ML experiments, and developing novel methodologies.
• Execute collaborative efforts with other teams to assess national security risks, including cybersecurity, biosecurity, and chemical weapons.
• Build and maintain experiment infrastructure, including evaluation software and tools.
• Communicate AI concepts and findings to key government stakeholders.

All applicants must submit a resume NOT TO EXCEED two pages on standard-size paper. If the resume exceeds two pages, only the first two pages will be reviewed for qualifications or assessment determinations.

Basic Requirements:
Experience must be IT related; the experience may be demonstrated by paid or unpaid experience and/or completion of specific, intensive training (for example, IT certification), as appropriate. For all positions individuals must have IT-related experience demonstrating each of the four competencies listed below. The employing agency is responsible for identifying the specific level of proficiency required for each competency at each grade level based on the requirements of the position being filled.

• Attention to Detail – Is thorough when performing work and conscientious about attending to detail.
• Customer Service – Works with clients and customers (that is, any individuals who use or receive the services or products that your work unit produces, including the general public, individuals who work in the agency, other agencies, or organizations outside the Government) to assess their needs, provide information or assistance, resolve their problems, or satisfy their expectations; knows about available products and services;
  
  is committed to providing quality products and services.
• Oral Communication – Expresses information (for example, ideas or facts) to individuals or groups effectively, taking into account the audience and nature of the information (for example, technical, sensitive, controversial); makes clear and convincing oral presentations; listens to others, attends to nonverbal cues, and responds appropriately.
• Problem Solving – Identifies problems; determines accuracy and relevance of information; uses sound judgment to generate and evaluate alternatives, and to make recommendations.

ZP-2210-IV: In addition to the basic requirements, applicants must have one year (52 weeks) of specialized experience equivalent to at least the GS-12 level (ZP-III at NIST). Specialized experience is defined as experience demonstrating technical understanding of machine learning or software engineering principles and best practices; carrying out technical AI research or building software systems and infrastructure; and contributing to technical projects in a team environment.

ZP-2210-V: In addition to the above requirements, applicants must have one year (52 weeks) of specialized experience equivalent to at least the GS-14 level (ZP-IV at NIST). Specialized experience is defined as experience demonstrating advanced technical expertise in machine learning or software engineering principles and best practices; designing AI research methodologies or software…