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Team Management

See listing · Turing · remote

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CheckedStatusSlots leftChangeHow
27 Oct 2026Open––Script, platform’s board
26 Oct 2026Open––Script, platform’s board
25 Oct 2026Open––Script, platform’s board
24 Oct 2026Open––Script, platform’s board

The script reads the platform’s own job board every night. A job not confirmed for 10 days comes off the list.

Most people who don't get in fail the screening, not the CV. Five minutes here first: How to pass the Turing assessment and interviews.

What the work is

About the Role

We are seeking highly qualified Team Management professionals to support the evaluation, testing, and continuous improvement of advanced Large Language Models (LLMs).

In this role, you will apply your expertise in team leadership, people management, performance management, workforce planning, and operational execution to assess AI-generated responses. You will identify knowledge gaps, design challenging real-world prompts, evaluate model reasoning, and help improve the accuracy, reliability, and practical usefulness of AI systems.

Key Responsibilities

  • Create complex, domain-specific prompts to test LLM capabilities.
  • Evaluate AI-generated responses for factual accuracy, reasoning, relevance, and overall quality.
  • Identify factual errors, logical inconsistencies, knowledge gaps, and model weaknesses.
  • Develop challenging test cases and edge cases that expose model limitations.
  • Provide clear, detailed, and evidence-based feedback to improve model performance.

Who gets hired

  • Master’s degree or higher in a relevant field.
  • At least three years of professional, research, or teaching experience.
  • Excellent written English communication skills.
  • Strong analytical and critical-thinking abilities.
  • Exceptional attention to detail.

Preferred Qualifications

  • Experience working with LLMs or Generative AI.
  • Familiarity with prompt engineering, AI evaluation, or model testing.
  • Experience designing challenging prompts, identifying edge cases, or stress-testing AI models.

Ideal Candidate

The ideal candidate is curious, detail-oriented, and deeply knowledgeable in their field. They enjoy solving complex problems, challenging assumptions, and identifying subtle factual or reasoning errors. Experience designing prompts that uncover model limitations and improve AI performance will be a strong advantage.

The platform posted this on 22 Oct 2026.

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