I help AI systems understand questions better by evaluating, refining, and improving how large language models (LLMs) interpret and respond to human input.
I specialize in Human-in-the-Loop (HITL) AI training, focusing on structured evaluation, data quality, and prompt refinement to improve model accuracy, reasoning, and instruction adherence.
My core services include:
• LLM response evaluation and grading
• AI output quality assurance (QA)
• Data annotation and text labeling
• Prompt evaluation and prompt optimization
• NLP content review
• Conversational AI testing
• AI alignment and instruction-following checks
• Structured feedback documentation
I work with detailed rubrics and evaluation frameworks to assess:
Accuracy and factual consistency
Logical reasoning and coherence
Instruction compliance
Tone and contextual alignment
Bias, ambiguity, and edge cases
With a background in procurement and operations, I bring analytical thinking, structured documentation, and high attention to detail into AI model evaluation workflows. I am comfortable identifying subtle reasoning gaps, constraint violations, and real-world context issues that automated systems often miss.
If you are building or improving:
Large Language Models (LLMs)
Conversational AI systems
Chatbots
Generative AI applications
AI-powered tools
I can support your team by delivering consistent, high-quality evaluation work that strengthens training data and improves model performance.
Reliable. Structured. Detail-oriented.
Focused on clarity, alignment, and measurable improvement.
