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About the Role

This role puts you on the measurement frontier: you won’t just observe the cutting edge, your work will define what cutting edge means. We’re hiring Members of Technical Staff (Applied AI Research) to design the evaluations that set the standard for how AI is measured: building novel benchmarks and datasets, evaluating every major model as it releases, working with the frontier labs on pre-release models before the world sees them, and publishing the analysis that labs, enterprises, media and policymakers rely on. The bar for success is becoming a world expert in modern AI. This is applied research with immediate industry consequence: shorter cycles than academia, more rigor than industry commentary, and a bigger audience than both. The center of the role is building: the large majority of your time goes to designing and shipping evaluations, with analysis and industry collaboration built around that work.

Responsibilities

Design Frontier Evaluations: Conceive, build and ship novel evaluation methodologies that advance how AI capabilities are measured, and that stay ahead of what frontier models can do
Build Evaluation Datasets and Infrastructure: Construct the datasets, harnesses and scoring systems behind our benchmarks, engineered for contamination resistance and repeatability at frontier scale
Evaluate Every Major Model: Run our evaluation suite across frontier releases as they land, and own the integrity of the results the industry quotes
Publish Influential Analysis: Produce the reports, indexes and data visualizations that shape how labs, enterprises and the broader industry understand AI 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
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

Requirements

3+ years of relevant professional experience, across industry or research
Intense interest in AI, a desire to become a world expert in the field, and strong analytical and coding skills
Hands-on experience with modern AI systems and understand how models work at a technical level
Know how to structure ambiguous problems, build analytical frameworks, and communicate findings to senior stakeholders
Genuine technical interest in AI and the ability to code
You follow model releases, you have opinions on where the technology is heading, and you want to be closer to the subject matter than consulting allows
Built and shipped AI products in a fast-moving environment, operating across research, engineering, product and commercial work simultaneously
Strong analytical and critical thinking skills
Proficiency in Python and data analysis
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

Skills

Python
data analysis
AI
Machine Learning
coding

Location

San Francisco

Work Type

on-site

Experience Level

3+ years

Benefits

Competitive compensation including equity

About the Company

Artificial Analysis is the leading independent AI benchmarking company.
We support labs, engineers and enterprises to understand AI capabilities and make critical decisions about their AI strategies.
We are the go-to authority for understanding AI, from AI labs and enterprises to media, investors, and policymakers.
Our benchmarks don’t just measure the cutting edge of AI, they are actively shaping the frontier.
Our benchmarks and analysis are trusted by hundreds of thousands of users and are the go-to reference for leading AI labs including OpenAI, Google, Meta, NVIDIA and Anthropic, and major publications including the Wall Street Journal, Bloomberg, the Financial Times and The Economist.
We are a team of 40+, on track to double by end of year, backed by Nat Friedman (GitHub, Meta), Daniel Gross (SSI, Meta), Andrew Ng (Google Brain, DeepLearning.ai, Amazon), Adam D’Angelo (Quora, Poe, OpenAI), Clem Delangue (Hugging Face) and other industry leaders.