Freelance AI QA Trainer - LLM Evaluation
Meridial Marketplace, by Invisible
Job Overview
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Job Description
About the Role: Freelance AI QA Trainer - LLM Evaluation
Are you an AI QA expert eager to shape the future of AI? Large-scale language models are evolving from clever chatbots into enterprise-grade platforms. With rigorous evaluation data, tomorrow’s AI can democratize world-class education, keep pace with cutting-edge research, and streamline workflows for teams everywhere. That quality begins with you—we need your expertise to harden model reasoning and reliability.
We’re looking for Freelance AI QA Trainers - LLM Evaluation who live and breathe model evaluation, LLM safety, prompt robustness, data quality assurance, multilingual and domain-specific testing, grounding verification, and compliance/readiness checks. You’ll challenge advanced language models on tasks like hallucination detection, factual consistency, prompt-injection and jailbreak resistance, bias/fairness audits, chain-of-reasoning reliability, tool-use correctness, retrieval-augmentation fidelity, and end-to-end workflow validation—documenting every failure mode so we can raise the bar.
What You'll Do
- Converse with the model on real-world scenarios and evaluation prompts.
- Verify factual accuracy and logical soundness.
- Design and run test plans and regression suites.
- Build clear rubrics and pass/fail criteria.
- Capture reproducible error traces with root-cause hypotheses.
- Suggest improvements to prompt engineering, guardrails, and evaluation metrics (e.g., precision/recall, faithfulness, toxicity, and latency SLOs).
- Partner on adversarial red-teaming, automation (Python/SQL), and dashboarding to track quality deltas over time.
What We're Looking For
A bachelor’s, master’s, or PhD in computer science, data science, computational linguistics, statistics, or a related field is ideal; shipped QA for ML/AI systems, safety/red-team experience, test automation frameworks (e.g., PyTest), and hands-on work with LLM eval tooling (e.g., OpenAI Evals, RAG evaluators, W&B) signal fit. Skills that stand out include: evaluation rubric design, adversarial testing/red-teaming, regression testing at scale, bias/fairness auditing, grounding verification, prompt and system-prompt engineering, test automation (Python/SQL), and high-signal bug reporting. Clear, metacognitive communication—“showing your work”—is essential.
Ready to turn your QA expertise into the quality backbone for tomorrow’s AI? Apply today and start teaching the model that will teach the world.
Compensation and Work Arrangement
We offer a pay range of $6-to- $65 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor you’ll supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply.
Employment type: Contract
Workplace type: Remote
Seniority level: Mid-Senior Level
Key skills/competency
- LLM Evaluation
- AI Safety
- Prompt Robustness
- Data Quality Assurance
- Adversarial Red-Teaming
- Hallucination Detection
- Bias/Fairness Auditing
- Test Automation (Python/SQL)
- Evaluation Rubric Design
- High-Signal Bug Reporting
How to Get Hired at Meridial Marketplace, by Invisible
- Research Meridial Marketplace/Invisible's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume for AI QA: Highlight experience in LLM evaluation, AI safety, prompt engineering, and test automation frameworks.
- Showcase relevant projects: Provide specific examples of model testing, adversarial red-teaming, or high-signal bug reporting.
- Prepare for technical discussions: Be ready to discuss evaluation metrics (e.g., precision/recall), RAG evaluators, and root-cause analysis.
- Demonstrate metacognitive communication: Clearly articulate your problem-solving process and how you 'show your work' in QA.
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