3 дня назад
Frost MetaBrain: AI Model Trainer - Business / Technology (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Frost MetaBrain: AI Model Trainer - Business / Technology (AI): Developing reusable, continuously updated software-enabled services by converting industry expertise, research methods, and business logic into structured AI learning and evaluation assets with an accent on evidence assessment, advisory quality, and controlled workflow improvements. Focus on designing evaluation rubrics, testing retrieval and business-rule changes, diagnosing model failures, and building Python evaluation scripts for the technology variant.
Location: Singapore (Hybrid)
Company
Frost & Sullivan combines decades of industry expertise, enterprise data, and third-party insights to deliver human-reinforced AI insights and analytics through MetaBrain.
What you will do
- Convert approved research methods, business logic, and advisory expertise into reusable MetaBrain learning assets.
- Curate research, taxonomies, decision rules, examples, counterexamples, and sourced reference answers.
- Create rubrics and evaluate advisory outputs for factual support, numerical consistency, relevance, completeness, and appropriate uncertainty.
- Run blind comparisons, document errors and reviewer disagreements, and maintain held-out evaluation cases.
- Configure prompts, retrieval settings, and business rules in approved environments, then retest versioned changes with rollback records.
- Partner with technical trainers on experiment design and failure diagnosis; the technology variant also includes Python evaluation scripts, dataset versioning, and approved fine-tuning experiments.
Requirements
- At least 3 years of hands-on research, consulting, or knowledge-quality experience, or equivalent achievement.
- Strong evidence assessment, business writing, numerical checking, and methodological attention to detail.
- Basic understanding of AI and large language models through formal learning or a certificate, plus a hands-on example of testing or improving AI outputs.
- Experience with peer review, analyst coaching, survey coding, taxonomy creation, quality assurance, low-code automation, or structured knowledge bases is preferred.
- SQL or Python is helpful for business-track applicants; Python evaluation scripting is required for the technology variant.
- Model-weight changes require approved data rights, engineering ownership, and regression testing.
Nice to have
- Peer review or analyst coaching experience.
- Survey coding, taxonomy creation, quality assurance, low-code automation, or structured knowledge-base experience.
- SQL or Python experience for business-track applicants.
Culture & Benefits
- Hybrid work in Singapore.
- Collaboration with AI/ML leads, technical trainers, domain mentors, and advisors.
- Work on continuously updated, software-enabled services combining research expertise with AI insights and analytics.
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