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Turing · Remote job

AI Benchmark & Red-Teaming Specialist

STEP 1 · PRACTICE FIRSTTake a free AI practice interview for this kind of roleGet my practice interview ↓
STEP 2 · APPLYApply on Turing when you’re readyApply on Turing →

You apply directly on Turing's site. Applying is free. Posted Oct 16, 2026.

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STEP 1 · PRACTICE BEFORE YOUR REAL INTERVIEW

Get your free practice interview for this role

Turing screens applicants online, often with an AI interview. micro1 offers a free, 18-minute AI practice interview with feedback, and we picked the one closest to this role: Data Annotator. It covers:

Instruction FollowingAttention to DetailLogical Reasoning

Here’s your practice interview

Allow your microphone when it asks, find a quiet spot, and give yourself about 20 minutes. We’ve also emailed you the link and the free ebook.

Step 2: when you feel ready, apply.

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The practice interview is free and run by micro1. Land Remote Jobs is an independent job board, not part of micro1, Mercor or Turing. Practising helps you prepare; it can’t guarantee the result of your real interview. Want more tips? Read our guide to acing the remote job interview.

STEP 2 · APPLY

Apply for this role

You apply on Turing's own site. It’s free, and you can apply even if you skip the practice.

Apply on Turing →

Who this role suits

Researchers and PhD holders who want to use their subject expertise on remote, flexible projects.

LLMQuality ManagementQA

Full job description

About Turing:
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.

Role Overview

We are seeking an analytical researcher and red-teaming specialist to build evidence-based web-research benchmark tasks that reliably expose weaknesses in state-of-the-art (SOTA) AI models (e.g., Claude Opus 5 Max). In this role, you will discover hard-to-surface facts, build precise research tasks around them, test them directly against leading LLMs, and diagnose the exact failure mechanisms in the model's search and reasoning paths.

Your work will directly shape AI evaluation frameworks, ensuring next-generation frontier models are tested against rigorous, non-trivial real-world research scenarios.

Job Requirements:

  • Core Experience: 1+ years in investigative research, fact-checking, AI benchmark task authoring, red-teaming, or technical QA review.
  • Benchmark Familiarity: Proven experience authoring, testing, or reviewing tasks for AI benchmarks such as GAIA, BrowseComp, SimpleQA, SWE-bench, Terminal-Bench, or Humanity’s Last Exam (HLE).
  • Analytical & OSINT Skills: Intermediate-to-advanced web search and Open Source Intelligence (OSINT) skills; ability to navigate academic archives, local records, or obscure databases.
  • Model Trajectory Debugging: Strong analytical capability to inspect model reasoning chains, search logs, and source selection to diagnose root causes of failure.
  • Precision Writing: Ability to author clear, unambiguous benchmark prompts with bulletproof, primary-sourced answer keys.

Job Responsibilities:

  • Obscure Fact Discovery: Deeply research niche topics to identify factual ground truths that cannot be surfaced via simple, direct search queries.
  • Source Verification: Rigorously verify facts against primary or highly credible sources, cross-check for contradictory evidence, and document exact source URLs.
  • Task Construction: Draft clear, answerable benchmark tasks designed specifically to expose structural weaknesses in model research strategies.
  • Red-Teaming & Model Testing: Execute tasks against designated SOTA models to confirm they reliably trigger intended model failures.
  • Failure Diagnosis & Debugging: Trace model run logs, search trajectories, and intermediate outputs to pinpoint exactly where and why the model failed (distinguishing genuine model limitations from ambiguous prompts).
  • Pattern Scaling & Review: Apply validated "model-breaking" research patterns across new domains and, for strong performers, review tasks authored by peer trainers.

    Strong Plus (Preferred Qualifications)
  • Bachelor or higher degree from relevant engineering domain is a must for this position.
  • Prior experience specifically designing prompt-injection or reasoning-trap tasks that break SOTA models.
  • Advanced OSINT capabilities or published investigative/academic research demonstrating deep source verification.
  • Niche domain expertise in areas rich with hard-to-find records (e.g., local government filings, regional sports history, legal archives, historical patents).
  • Experience serving as a lead reviewer, benchmark auditor, or quality owner on AI evaluation projects.

Offer Details:

  • Commitments Required: Upto 40 hours per week with 4 hours of overlap with PST.
  • Engagement type: Contractor
  • Engagement Length:  upto 4 weeks

Evaluation Process -

  • Candidates will be require to submit a Job Interest Form & assessment.
  • Talents finalized in assessment will go through assessment, review & will proceed further accordingly.

Last checked open on Oct 28, 2026. Job description provided by Turing.

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