Member of Technical Staff (Applied AI Research)

About Artificial Analysis

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 http://DeepLearning.ai, Amazon), Adam D’Angelo (Quora, Poe, OpenAI), Clem Delangue (Hugging Face) and other industry leaders.

The Opportunity

Our evaluations decide how the world measures AI. When a frontier lab ships a model, our benchmarks are how the industry finds out what it can actually do, and the labs themselves use our results to guide what they build next. 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.

What You’ll Do

• 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

What We’re Looking For

We require 3+ years of relevant professional experience, across industry or research. You have an intense interest in AI, a desire to become a world expert in the field, and strong analytical and coding skills to back it up.

Beyond that bar, we hire from three backgrounds. You should clearly fit one of these profiles

AI and Machine Learning

Backgrounds include: ML Engineer, ML Researcher, Research Engineer, AI Engineer, Forward Deployed Engineer, Technical PM, or similar roles at AI companies or AI-focused teams.

You have hands-on experience with modern AI systems and understand how models work at a technical level. You want your work to ship faster than a paper and matter more than a dashboard: evaluations the whole industry sees, on a cycle measured in days.

Strategy Consulting

Backgrounds include: Management Consultant, Associate, Engagement Manager, Data Scientist, or similar roles at firms like McKinsey, BCG, Bain, or equivalent. Strong preference will be given to candidates with experience within a Data Analytics division such as QuantumBlack, AI by McKinsey, BCG X or equivalent.

You know how to structure ambiguous problems, build analytical frameworks, and communicate findings to senior stakeholders. The key differentiator: 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.

Technical Product Management

Backgrounds include: Founding Engineer, Product Manager, Technical Co-founder, Head of Product, or generalist roles at early-stage AI companies.

You’ve built and shipped AI products in a fast-moving environment, operating across research, engineering, product and commercial work simultaneously. You’re looking for a role where that breadth is the job, not a side effect of being early at a small company.

Across all three profiles, we require

• 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

Why Artificial Analysis?

• Shape how AI gets built: The leading AI labs track our benchmarks and use them to guide their development priorities. Your work will directly influence the direction of AI.
• Become a world expert in AI: You will evaluate every major model, across every major capability, as they are released. Very few roles offer this breadth of exposure to frontier AI.
• Work with the most important players in AI: You’ll manage relationships with teams at the leading AI labs and major enterprises as a trusted, independent voice.
• Join at a defining moment: We’re 40+ people, on track to double by end of year, backed by some of the most connected investors in AI. The people who join now will shape the product, the team, and the strategy as we scale.
• Competitive compensation including equity

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