Simon Kahenya

Key Skills

Software

HiveMind

Labelbox

Remotasks

Scale AI

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Text

Top Label Types

Computer Programming Coding

Prompt Response Writing SFT

Question Answering

RLHF

Text Generation

Freelancer Overview

I am a 7+ years experienced AI model trainer, tester, and data annotator. I have trained LLMs, NLP, and computer vision models during my career. My career has involved fine-tuning AI models, large dataset annotation, and machine learning model optimization to achieve the optimal accuracy and efficiency. I have developed state-of-the-art AI models through my activities in reinforcement learning from human feedback (RLHF), prompt engineering, and text generation optimization. I have extensive experience with model interpretability, bias detection, and AI ethics. Having a Ph.D. in Mathematics and Computer Science and working at leading AI research institutions such as Google DeepMind and Microsoft Research, my technical background includes data curation, annotation process with structured annotation, and LLM benchmarking to train AI models using high-quality, consistent data. An enthusiast of AI innovation, I am devoted to cultivating machine learning capabilities through scientific research and data-driven optimization.

Labeling Experience

LLM Training and Reinforcement Learning with Human Feedback (RLHF)

AppenTextText GenerationTracking

Helped develop and evaluate large language models (LLMs) by annotating AI-generated responses for accuracy, coherence, and ethical concerns. Supported RLHF-based AI improvement, wherein I provided response ranking, prompt engineering, and data curation to improve AI-generated text. Task was to identify biases, improve factual grounding, and refine AI responses for real-world usability. Ensured high-quality annotations through cross-validation, inter-annotator agreement, and rigorous AI evaluation processes.

Helped develop and evaluate large language models (LLMs) by annotating AI-generated responses for accuracy, coherence, and ethical concerns. Supported RLHF-based AI improvement, wherein I provided response ranking, prompt engineering, and data curation to improve AI-generated text. Task was to identify biases, improve factual grounding, and refine AI responses for real-world usability. Ensured high-quality annotations through cross-validation, inter-annotator agreement, and rigorous AI evaluation processes.

2021 - 2024

Education

Work History