[Hiring] Research Scientist @Anyone AI

Role Description

You will own how Anyone AI measures frontier model capability. This is a research role at heart: you decide what a good evaluation is, design the benchmarks that prove it, and defend the methodology under lab scrutiny. You'll build frontier-grade evaluation packages across reasoning, coding, agents, tool use, and multi-modal — grounded in expert-verified truth, validated against multiple models, and QC'd to survive buyer-side review.

Responsibilities

• Evaluation research: Turn public benchmarks and eval targets into original evaluation designs. Own the hard questions: construct validity, discrimination, headroom, and contamination.
• Benchmark development: Build evaluation packages with subject-matter experts, each with expert-verified ground truth, multi-model headroom results, and rigorous QC (calibration layers, severity-weighted rubrics, deterministic verifiers).
• Experts: Recruit, calibrate, and review a pool across coding, agentic/tool-use, and STEM/reasoning. Be the final arbiter of correctness and frontier difficulty.
• Lab relationships: Be a technical point of contact for labs, with CEO support. Understand what they're trying to measure and translate it into an evaluation design.
• Delivery: Turn lab requests into winning sample packages, then own pilots end to end. Nothing ships before it's lab-ready.

Qualifications

• Research background in ML evaluation or benchmarking — published/open benchmarks, eval research, or equivalent hands-on work labs relied on.
• Deep LLM benchmarking expertise, with real strength in code-model evaluation.
• Fluency with how frontier models are measured: rubrics, pass rates, headroom, contamination, and what makes a task discriminate a model.
• Proven ability to hold a team or expert pool to a rigorous standard.
• Fluent English. Spanish a nice to have.