Lavender T.

Key Skills

Software

Scale AI

iMerit

Top Subject Matter

Conversational AI

Nlp Domain Expertise

Content Safety

Top Data Types

Text

Document

Top Task Types

RLHF

Entity (NER) Classification

Freelancer Overview

Generalist AI Trainer (RLHF & LLM evaluation) | Scale AI (Remotask) | Contract. Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Scale AI, iMerit, and Uber AI Evaluation Tools. Education includes Diploma in Information Technology, Meru Technical College (2025). AI-training focus includes data types such as Text and labeling workflows including RLHF, Entity (NER) Classification, and Evaluation.

Labeling Experience

Generalist AI Trainer (RLHF & LLM evaluation) | Scale AI (Remotask) | Contract

Scale AITextRLHF

Provided RLHF, LLM evaluation, response ranking, and training data generation for large-scale AI model development pipelines using structured rubrics. Evaluated AI-generated responses for accuracy, tone, helpfulness, safety, and guideline compliance, including complex edge cases with consistent judgment. Completed preference ranking by comparing side-by-side model outputs and writing justifications aligned to defined quality criteria. • Compared model outputs and selected the better response using explicit RLHF quality criteria. • Performed binary classification, structured scoring, and categorization across customer service and conversational AI interactions. • Identified and documented hallucinations, misleading content, unsafe outputs, and policy violations for downstream decisions. • Contributed multilingual (English/Swahili) dataset support with culturally grounded context for diverse users.

2024 - 2025

AI Data Evaluator | Uber AI | Contract

Text

Assessed AI-generated responses for conversational and support-focused model improvement using structured evaluation and feedback outputs. Rated factual accuracy, clarity, helpfulness, tone appropriateness, and cultural fit for diverse user groups, grounded in user-impact considerations. Produced structured written feedback describing failure patterns and guidance for engineering teams to improve response behavior. • Evaluated response quality dimensions including accuracy, helpfulness, tone, and clarity. • Authored structured feedback to help teams identify gaps and understand how responses land with real users. • Delivered deadline-focused outputs consistently over extended project periods. • Supported iterative improvement of conversational/support AI models through documented observations.

2024 - 2024

AI Data Specialist | iMerit | Contract

iMeritTextEntity (NER) Classification

Performed NLP annotation, intent and sentiment labeling, conversational quality labeling, and content moderation QA for conversational AI and safety pipelines. Applied domain-specific annotation guidelines precisely, escalating ambiguous cases through QA channels while maintaining workflow pace. Participated in multi-pass QA review processes to maintain dataset integrity before ingestion. • Labeled conversational datasets for intent, sentiment, tone, and response quality to meet strict quality thresholds. • Completed content safety and moderation annotations to detect harmful, misleading, and policy-violating text across varied content types. • Reviewed and corrected prior annotations in multi-pass QA workflows to preserve consistency at scale. • Escalated unclear edge cases via appropriate QA procedures without disrupting production delivery.

2023 - 2023

Education

Work History