Research Scientist (Remote/US/LATAM)

About this role

Research Scientist, Evaluations

Anyone AI Labs — Human Data Division
Reports to: CEO · Remote / LatAm / US

The role

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.

What we're looking for

- 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.