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Llm Quality Reviewer Jobs (NOW HIRING)

SME Careers

Filipino / Tagalog Team Lead

Skills & Technologies English Filipino Translation Quality Review Localization QA LLM Evaluation AI Training Filipino Quality Assurance Tagalog Trainer Feedback style guides

Hippocratic AI

RN/NP Clinical Quality Reviewer

RN/NP Clinical Quality Reviewer Primary Care, Acute Symptom Triage & Travel Health | Contract, up ... We're building the world's first healthcare‑only, safety‑focused LLM -- a breakthrough platform ...

Elsevier

Senior ML Ops Engineer

$112K - $179K/yr

Buildevaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness ... They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$112K - $179K/yr

Buildevaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness ... They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These ...

RELX

Senior ML Ops Engineer

Philadelphia, PA · On-site

$112K - $179K/yr

Buildevaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness ... They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These ...

RELX

Senior ML Ops Engineer

$112K - $179K/yr

Buildevaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness ... They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$112K - $179K/yr

Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness ... They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These ...

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Llm Quality Reviewer information

What is an LLM Quality Reviewer?

LLM Quality Reviewers are professionals who evaluate the outputs of large language models (LLMs) to ensure accuracy, relevance, and adherence to guidelines. Their responsibilities include reviewing generated content, detecting biases or errors, and providing feedback to improve model performance. They play a crucial role in maintaining the quality and reliability of AI-generated responses, often collaborating with data scientists and engineers. This position typically requires strong analytical skills, attention to detail, and familiarity with AI technologies.

What are the key skills and qualifications needed to thrive as an LLM Quality Reviewer, and why are they important?

To thrive as an LLM Quality Reviewer, you need a strong background in linguistics, natural language processing, and thorough understanding of large language models, typically supported by a relevant degree or experience in AI or computer science. Familiarity with annotation tools, model evaluation frameworks, and platforms like Python or SQL is important for assessing and improving model outputs. Attention to detail, critical thinking, and clear communication enable effective feedback and collaboration with development teams. These skills ensure accurate evaluation, improved model performance, and alignment with project goals in the fast-evolving AI landscape.

What are some typical challenges faced by LLM Quality Reviewers, and how can they be addressed?

LLM Quality Reviewers often encounter challenges such as evaluating large volumes of AI-generated content under tight deadlines and ensuring consistent application of complex evaluation guidelines. Attention to detail and strong communication skills are essential, as is the ability to provide actionable feedback to model developers. Collaborating closely with data scientists and engineers helps reviewers stay aligned on quality standards and resolve ambiguities promptly. Developing a systematic approach to reviews and staying updated on evolving best practices can make the role more manageable and rewarding.

What is the difference between Llm Quality Reviewer vs Data Annotator?

AspectLlm Quality ReviewerData Annotator
Required CredentialsBasic understanding of AI/ML concepts, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or office-based, focused on reviewing AI outputsRemote or office-based, focused on labeling data
Employer & IndustryTech companies, AI/ML industryTech companies, data labeling services
Search & Comparison IntentUnderstanding quality review roles in AIUnderstanding data labeling roles in AI

The main difference between an Llm Quality Reviewer and a Data Annotator is that the reviewer assesses and ensures the quality of AI-generated outputs, while the annotator labels and prepares data for training AI models. Both roles require attention to detail and are common in AI/ML industries, but the reviewer focuses on evaluating existing outputs, whereas the annotator creates the training data.

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Llm Quality Reviewer jobs near you
Infographic showing various Llm Quality Reviewer job openings in the United States as of September 2026, with employment types broken down into 2% As Needed, 80% Full Time, 14% Part Time, 3% Contract, and 1% Nights. Highlights an 83% Physical, 1% Hybrid, and 16% Remote job distribution.

Filipino / Tagalog Team Lead

Remote

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Re-posted 4 days ago

Job description

Job Title

Job Description

Required Skills and Experience

Bachelor's or Master's degree in Filipino, Tagalog, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field.

Native or near-native Filipino/Tagalog proficiency with strong reading and writing skills.

Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear feedback in English.

3+ years of professional experience in Filipino/Tagalog writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows.

Strong understanding of Filipino/Tagalog grammar, spelling conventions, punctuation, tone, register, cultural context, and natural usage.

Comfortable handling formal Filipino, conversational Tagalog, and Taglish/code-switching when required, while keeping style consistent with project guidelines.

Ability to evaluate Filipino/Tagalog content against detailed rubrics and identify issues such as mistranslation, literal phrasing, unnatural tone, incorrect code-switching, hallucinated claims, ambiguity, or inconsistent terminology.

Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is strongly preferred.

Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.

Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and other quality documentation.

Experience with AI training, data annotation, large language models, prompt/response evaluation, or rubric-based LLM QA is a strong plus.

Key Responsibilities

Quality monitoring: Spot-check Filipino/Tagalog items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.

Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, and quality expectations.

Question handling: Respond to trainer/QA questions clearly and promptly, especially around Filipino/Tagalog wording, tone, register, translation fidelity, Taglish usage, cultural context, and edge cases.

Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.

Documentation: Create and maintain Filipino/Tagalog project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, and onboarding materials.

Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and Filipino/Tagalog-specific style requirements.

Quality alignment: Ensure all trainers and QAs apply Filipino/Tagalog language guidelines consistently and understand updates as projects evolve.

Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for Filipino/Tagalog-language projects.

Skills & Technologies

English Filipino Translation Quality Review Localization QA LLM Evaluation AI Training Filipino Quality Assurance Tagalog Trainer Feedback style guides

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