Advanced Semantic Annotation: Experienced in context-aware text labeling, entity extraction, intent classification, and
Advanced Semantic Annotation: Experienced in context-aware text labeling, entity extraction, intent classification, and multi-turn conversational dialogue tagging for natural language processing (NLP) systems.Multimodal Data Categorization: Skilled in cross-referencing textual descriptions with audio visual datasets, utilizing strict taxonomy rules to classify complex metadata accurately.RLHF & Model Evaluation: Proven ability to create diverse prompt datasets, critique and rank LLM outputs, and compose comprehensive, rule-based rationales detailing response flaws or merits.Factual Verification & Audit: Expert at executing deep-dive research to verify historical, mathematical, or technical data points, weeding out hallucinations and factual inconsistencies.Quality Control & Tool ProficiencyEdge Case Identification: Highly proficient at identifying ambiguous datasets and documenting unique edge cases to refine training taxonomies for engineering teams.Platform & Workspace Tools: Hands-on experience with widespread industrial labeling interfaces, collaborative remote environments, and web-based annotation sandboxes.High QA Benchmarks: Consistently maintained independent Quality Assurance (QA) accuracy ratings between 93% and 98% across varying project disciplines.If you would like to expand on this, I can:Rewrite your CV experience section to incorporate these specific intermediate-level bullet points.Draft a highly technical sample prompt evaluation to demonstrate your intermediate capabilities during your platform assessment.Let me know how you want to proceed.