Safety and security

Capability evaluation and benchmarking

Capability evaluation and benchmarking is the work of measuring what AI systems can actually do and where they fail. AI companies need it to decide what to ship, what to fix and what to hold back.

Models now ship faster than the tests that judge them. Founders face questions about quality, risk and fitness for a customer's work, and a leaderboard score rarely answers them. The hires are tricky because the skill sits between disciplines. A strong candidate has the rigour of an experimental scientist, the habits of a software tester and enough domain sense to know when a test measures the wrong thing. Many people claim it. Few can show a valid test.

Hiring now 4Emerging 1

Roles in this family

5 roles

Where the people come from

Experimental science, statistics, software testing or domain evaluation

Not to be confused with. Benchmark performance is not a universal measure of intelligence or safety.

Core skills

  • Probability and statistics
  • Experimental design
  • Data quality and provenance
  • Model evaluation

Where it is used

  • Cross-sector AI platforms
  • Frontier AI governance

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