LLM- Prompt Analysis for AI Study Assistant
Providing metadata and prompt analysis and categorization for the training of a AI Study Assistant.
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Native Spanish Communications professional and language enthusiast with over 1.5 years of experience in AI training for LLMs. Projects have included: AI Data Training & Evaluation Projects Prompt and Response Writing: Authored high-quality prompts and model responses demonstrating ideal reasoning and style across diverse tasks. Localization: Adapted prompts and responses for linguistic, cultural, and regional accuracy in multilingual projects. RLHF: Ranked and annotated model outputs based on helpfulness, factuality, clarity, tone, and safety to train reward models. SFT: Created and curated instruction–response pairs illustrating ideal answers and reasoning for supervised fine-tuning. Rubric Development (SFT & RLHF): Designed response rubrics defining the key features of high-quality outputs to guide annotators and ensure alignment consistency. Safety & Red Teaming: Evaluated model behavior for policy compliance and created adversarial prompts to test safety boundaries. Adversarial Evaluation: Conducted stress tests and edge-case evaluations to identify reasoning flaw Experience spans both general-purpose LLM and subject matter expertise (SME) contributions for Business and Advertising domains. Full CV available on request.
Successfully completed audio recordings with good quality.
Providing metadata and prompt analysis and categorization for the training of a AI Study Assistant.
Audio Analysis: Assessed audio interactions with AI generated voices for accuracy, intent recognition, and multimodal context handling.
Creating training data sets for AI models that will help improve their accuracy, fluency, coherence and/or voice. Image-related Prompt Authoring (ITV, VTV, TTI, TTV): Developed and evaluated prompts for image-to-text and text-to-visual generation tasks.
Authored creative and domain-specific prompts targeting model weaknesses in marketing, branding, and advertising (creativity, understanding of metrics, cultural nuances, non-generic/on-brand messages). Evaluated model outputs for tone, persuasiveness, and adherence to brand voice and campaign objectives. Provided expert linguistic feedback to improve model creativity and cultural nuance. Supported training of GenAI systems through targeted prompt optimization and qualitative evaluations.
Annotated and validated model outputs under reinforcement learning and supervised fine-tuning frameworks. Applied linguistic and contextual expertise to improve bilingual model fluency, clarity, and factual grounding. Response Personalization. Evaluation of Live Mode Assistants in several task categories.
Introduction to Conversation Design, AI
Postgraduate, Fashion and Luxury Goods Management
Bilingual AI trainer for LLMs
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