Researcher, Research​/Development, AI Evaluation

Core Areas: AI Capabilities Research, AI Trends Analysis, Quantitative Research, AI Benchmarking, Data Center Research, AI Compute Supply Chains, Statistical Analysis, Research Methodology

Compensation: $115,000-$185,000 USD annually

Schedule: Flexible working hours for most roles; preference for availability overlapping Pacific Time (UTC−8) and Greenwich Mean Time (UTC).

Travel: Ability to attend three organizational retreats per year is preferred.

About the Role

This Researcher opportunity focuses on investigating artificial intelligence capabilities, identifying technological trends, and evaluating the factors shaping AI development and its broader impact. The position involves conducting quantitative and qualitative research, improving analytical methodologies, producing data-driven reports, and developing evidence-based forecasts. Researchers also contribute to defining research priorities and exploring emerging questions about AI progress.

Research opportunities span AI data centers, semiconductor supply chains, AI adoption and impacts, benchmark evaluation, and model capability trends. Depending on the research area, responsibilities may include analyzing compute infrastructure, designing behavioral studies, reviewing AI benchmarks, developing data explorers, investigating scaling laws, or conducting experiments on AI models. The role requires rigorous analytical reasoning, intellectual curiosity, and the ability to communicate complex research findings clearly.

What You'll Do
Data Center Research

• Investigate frontier AI data centers and produce quantitative insights, research reports, and structured datasets on AI computing infrastructure.
• Improve research methodologies used to collect, assess, and present information about AI data centers.
• Examine data center development across countries, including infrastructure expansion, capacity constraints, and factors affecting future construction.
• Develop estimates of semiconductor and AI accelerator deployments within individual data centers.
• Depending on project needs and role fit, coordinate contractors responsible for researching individual data centers.

AI Supply Chain Research

• Investigate the global supply chain supporting AI compute infrastructure, including semiconductor components, chip ownership, and hardware utilization.
• Analyze the geographic distribution of AI chips, identify organizations using these resources, and examine how computing infrastructure is financed.
• Assess emerging patterns in AI hardware investment, hyperscaler capital expenditure, and the future availability of AI compute resources.
• Develop research outputs such as interactive data explorers, analytical insights, and detailed technical or industry reports.

AI Impacts Research

• Investigate the economic, behavioral, and strategic impacts of artificial intelligence.
• Study AI-related productivity improvements, adoption patterns, and changes in the broader strategic landscape.
• Design and analyze surveys, randomized controlled trials (RCTs), and other behavioral datasets related to AI usage.
• Apply quantitative reasoning and empirical evidence to evaluate the effects and potential trajectories of AI technologies.

AI Benchmark Review

• Research and evaluate the quality, reliability, and methodological soundness of benchmarks used to measure AI capabilities.
• Review individual benchmarks and prepare public-facing analyses explaining evaluation findings.
• Contribute to benchmark review and certification efforts.
• Potentially develop guidance for creating stronger AI benchmarks and contribute directly to benchmark development.

AI Capability Trends Research

• Maintain, improve, and expand research projects that measure AI model capabilities and long-term performance trends.
• Analyze changes in AI capability trajectories, including potential trend breaks and acceleration patterns.
• Investigate statistical relationships between AI performance, computational resources, and model scaling laws.
• Explore methods for incorporating inference compute into scaling-law analysis.
• Design or conduct experiments involving AI models to improve understanding of their capabilities and development trajectories.
• Contribute to ongoing research on AI progress through empirical analysis, methodological improvements, and new research directions.

Qualifications
Required Skills

• Strong quantitative reasoning skills, including the ability to develop estimates from incomplete information and evaluate uncertainty systematically.
• Ability to absorb unfamiliar technical or…