Creative Writers - Freelance AI Trainer at Mindrift

, , Singapore -

Full Time

Start Date

Immediate

Expiry Date

05 May, 26

Salary

25.0

Posted On

04 Feb, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Creative Writing, Conversational AI Testing, Narrative Design, Adversarial Model Testing, Emotional Intelligence, Instruction-Following, Documentation, Conversational Pressure, Storytelling, Human Dialogue, LLM Evaluation, Behavioral Research, Psychology, Linguistics, QA Testing, Prompt Engineering

Industry

technology;Information and Internet

Description

Please submit your resume in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves This project requires you to put yourself in the position of a range of different user personas and engage in realistic multi-turn conversations with LLMs, working towards a clearly defined goal. You will need to: use a range of tones and registers, stress-test the models’ ability to respond adequately based on several abstract dimensions (e.g. instruction-following, emotional intelligence, consistency under changing constraints), and react and adapt to model output while maintaining tight focus on each individual task’s requirements. Think of yourself as a controlled adversary, crafting plausible human dialogue that exposes subtle model weaknesses while maintaining narrative coherence. For this, you will need to: Think like a storyteller and a tester Understand how humans actually speak, hesitate, contradict themselves, and escalate emotionally Be able to deliberately engineer conversational pressure without breaking realism Be methodical enough to document observations clearly and consistently Be able to pinpoint failure modes and LLM patterns What we look for This opportunity is a good fit if you are seeking for open to part-time, non-permanent projects. Ideally, contributors will have: an under- or postgraduate qualification in an Arts-based subject (English, Creative Writing, Journalism, MFL, Psychology, Cognitive Science), related field, or work experience at an equivalent level; or 1+ years’ experience in Conversational AI Testing, Narrative Design, or Adversarial Model Testing C2-level English (CPE, TOEFL 114+, IELTS 8.0 or above) Nice to have Conversational UX / dialogue design experience An understanding of prompt engineering or LLM evaluation Experience with QA testing for complex systems A background in narrative design, interactive fiction, or screenwriting A qualification in, or professional experience with, behavioural research, psychology, or linguistics Demonstrated familiarity with LLM behaviour, failure modes, and evaluation concepts Experience working with structured guidelines, rubrics, or annotation frameworks You will receive training in our guidelines and in how to create structured, focused conversations that meet the project’s goals. You will also be assigned a mentor who will guide you through your first conversations and provide clear, actionable feedback to support your improvement. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Payment Paid contributions, with rates up to $25/hour* Fixed project rate or individual rates, depending on the project Some projects include incentive payments *Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.

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Responsibilities

You will engage in realistic multi-turn conversations with LLMs, testing their responses based on various dimensions. The role involves crafting human dialogue to expose model weaknesses while maintaining narrative coherence.