Job Description - Member of Technical Staff (Language Model Evaluations)

Location: San Francisco (preferred), Sydney, Melbourne, Brisbane

The Opportunity

Language model evaluation is the sharpest question in AI: what can these systems actually do? Our answers, from the Artificial Analysis Intelligence Index to AA-Omniscience, AA-Briefcase and our coding agent evaluations, are the reference the industry uses. We're hiring Members of Technical Staff to build the next generation of them.

This is a role for people who want to build frontier benchmarks: designing evaluations that stay ahead of frontier capabilities, constructing datasets that resist contamination, and measuring what everyone else has not yet worked out how to measure. You will run your work across every major model as it releases and publish results the whole industry reads.

The center of the role is building. Analysis and lab collaboration wrap around the evaluation work, with our commercial team owning client relationships day to day.

What You'll Do
• Design Next-Generation Frontier Evals: Conceive and ship the next generation of frontier evaluations, like AA-Briefcase and AA-Omniscience, across reasoning, knowledge, coding, agentic capability and beyond
• Build Evaluation Datasets and Infrastructure: Construct the datasets, harnesses and scoring systems behind our benchmarks, engineered for contamination resistance and repeatability at frontier scale
• Shape the Future Intelligence Index: The evaluations you build will contribute to future versions of the Artificial Analysis Intelligence Index and other areas of our platform, defining how the industry measures frontier capability
• Publish Influential Analysis: Produce the reports, indexes and data visualizations that shape how the industry understands language model progress
• Work with Frontier Labs on Pre-Release Models: Benchmark the leading labs' systems, including pre-release and newly launched models, working directly with their research teams; our commercial team owns client relationships day to day, so your time stays on the science
• Evaluate Every Major Model: Run our evaluation suite across frontier releases as they land, and own the integrity of the results the industry quotes
• Become AI-Native: Embrace an AI-native workflow, using cutting-edge AI tools to generate leverage in a fast-changing industry and maintain our competitive edge in AI benchmarking

What We're Looking For

You have deep, hands-on experience evaluating language models and strong opinions about why most benchmarks fail.

Backgrounds include: evaluation and benchmarking teams at AI labs; research or engineering roles at evaluation-focused organizations; ML engineers who have built evaluation harnesses and datasets in production; or academic researchers in NLP and ML evaluation with a strong record of published work.

Required:
• 3+ years of relevant professional experience, across industry or research
• Strong analytical and critical thinking skills
• Strong Python, with hands-on experience running evaluation harnesses and building datasets
• Deep familiarity with the LLM evaluation landscape: the major benchmarks and their failure modes, contamination, preference-based methods, and agentic evaluation
• Strong statistical grounding: you know when a result is signal and when it is noise
• Genuine, demonstrable interest and knowledge of Frontier AI. We want people who have informed opinions about where AI is heading, not just people who use AI tools

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