AI QA Trainer – Freelance Project

Invisible Technologies

. Challenge advanced language models through model evaluation and testing .

Posted 10/31/2026contractRemote • SingaporeMid-LevelSenior💰 $6 - $65 per hourWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in model evaluation, prompt engineering, and data quality assurance, with a strong focus on LLM safety and compliance. Proficient in designing test plans, conducting regression testing, and utilizing automation frameworks to enhance model reliability and performance.

Highest-signal resume keywords

Model Evaluation ExpertiseTest Automation Using Python/SQLAdversarial Testing/Red-TeamingBias/Fairness AuditingEvaluation Rubric Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Model EvaluationPrompt EngineeringData Quality AssuranceRegression TestingHallucination DetectionFactual ConsistencyGrounding VerificationTest Automation FrameworksEvaluation Rubric DesignHigh-Signal Bug Reporting

Soft Skills

Clear CommunicationMetacognitive Communication

Tools & Technologies

PythonSQLPyTestOpenAI EvalsRAG EvaluatorsW&B

Certifications & Qualifications

Bachelor’s DegreeMaster’s DegreePhD in Computer ScienceData ScienceComputational LinguisticsStatistics

Industry Keywords

LLM SafetyPrompt RobustnessMultilingual TestingCompliance ChecksAdversarial Red-TeamingChain-of-Reasoning ReliabilityTool-Use CorrectnessRetrieval-Augmentation FidelityEnd-to-End Workflow ValidationBias/Fairness Audits

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Challenge advanced language models through model evaluation and testing
Converse with models on real-world scenarios and evaluation prompts
Verify factual accuracy and logical soundness
Design and run test plans and regression suites
Build rubrics and pass/fail criteria
Capture reproducible error traces with root-cause hypotheses
Suggest improvements to prompt engineering, guardrails, and evaluation metrics
Partner on adversarial red-teaming and automation using Python/SQL
Build dashboards to track quality changes over time
Document failure modes to improve model reasoning and reliability

Requirements

What you’ll need

Expertise in model evaluation, LLM safety, prompt robustness, data quality assurance, multilingual and domain-specific testing, grounding verification, and compliance/readiness checks
Experience with 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
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
Experience with test automation frameworks such as PyTest
Hands-on work with LLM evaluation tooling such as OpenAI Evals, RAG evaluators, and W&B
Evaluation rubric design
Adversarial testing/red-teaming
Regression testing at scale
Bias/fairness auditing
Grounding verification
Prompt and system-prompt engineering
Test automation using Python/SQL
High-signal bug reporting
Clear, metacognitive communication
Secure computer and high-speed internet as a contractor

Benefits

Comp & perks

Secure computer and high-speed internet supplied by contractor
Company-sponsored health insurance and PTO do not apply