AI Model Trainer, Business/Technology

Frost & Sullivan

. Teach and evaluate how MetaBrain applies approved research methods and business logic .

Posted 10/7/2026full-timeSingapore • SingaporeMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in research methods, evaluation, and business logic application, with a strong focus on quality assurance and attention to methodological detail. Proficient in Python evaluation scripting and capable of managing datasets and fine-tuning experiments.

Highest-signal resume keywords

Python Evaluation ScriptingResearch Methods ApplicationQuality AssuranceEvidence AssessmentTaxonomy Creation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Research MethodsEvidence AssessmentNumerical CheckingBusiness WritingMethodological DetailTaxonomy CreationSurvey CodingLow-Code AutomationDataset ManagementVersion Control

Soft Skills

Attention to DetailAnalytical ThinkingCollaborationCoaching

Tools & Technologies

SQLPythonDesign/Tuning Environments

Certifications & Qualifications

AI/Language Model Understanding Certificate

Industry Keywords

Peer ReviewKnowledge QualityQuality AssuranceStructured Knowledge BaseEvaluation Cases

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Teach and evaluate how MetaBrain applies approved research methods and business logic
Convert expert knowledge into structured examples, rules and review criteria
Turn advisor feedback into controlled, testable improvements
Curate authorized research, taxonomies, decision rules, examples and counterexamples
Create reference answers with supporting sources and record scope, dates, limitations and permitted use
Write rubrics for factual support, numerical consistency, relevance, completeness and appropriate uncertainty
Run blind comparisons and document errors, reviewer disagreements and adjudication
Keep held-out evaluation cases separate
Configure prompts, retrieval settings and business rules in approved Design/Tuning environments
Turn advisor corrections into versioned change requests
Retest after each update and retain a clear rollback record
Partner with technical trainers on experiment design and failure diagnosis
For the technology variant, build Python evaluation scripts, manage dataset versions and support approved fine-tuning experiments where justified

Requirements

What you’ll need

Substantial hands-on research, consulting or knowledge-quality experience; typically 3+ years, with equivalent achievement considered
Strong evidence assessment, business writing, numerical checking and attention to methodological detail
Basic understanding of AI/large language models from formal learning or a certificate and a hands-on example of testing or improving AI outputs
Preferred: Experience in peer review, analyst coaching, survey coding, taxonomy creation, quality assurance, low-code automation or maintaining a structured knowledge base
SQL or Python is helpful for business-track applicants
Python evaluation scripting is required for the technology variant