For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

Invite to Job
K
Kimani J.

Kimani J.

Kenya flagNairobi, Kenya

Key Skills

Software

No software listed

Top Subject Matter

No subject matter listed

Top Data Types

ImageImage
VideoVideo
TextText

Top Task Types

Bounding BoxBounding Box
PolygonPolygon
Point/Key PointPoint/Key Point
Entity (NER) ClassificationEntity (NER) Classification
SegmentationSegmentation
CuboidCuboid

Freelancer Overview

My AI training and data evaluation experience is rooted in Reinforcement Learning from Human Feedback (RLHF) and rigorous model benchmarking. Working as an AI Data Trainer and Evaluator, my primary focus has been providing high-quality human feedback to train Large Language Models (LLMs) to ensure safety, accuracy, and strict adherence to complex prompts. I routinely evaluate AI-generated responses against comprehensive truthfulness and helpfulness rubrics, specifically identifying edge cases, logical flaws, and model hallucinations to improve overall system reliability. In addition to direct model evaluation, I have hands-on experience with large-scale data labeling and categorization designed to sharpen machine learning algorithms. I analyze emerging behavioral patterns to assist developers in refining automated filtering systems, particularly for detecting spam and malicious intent. Ultimately, my work bridges the gap between raw data and refined AI behavior, ensuring models are both highly precise and safe for user interaction.

Labeling Experience

Here is a natural, professional paragraph detailing your specific experience that you can use to answer this: In my exp

Here is a natural, professional paragraph detailing your specific experience that you can use to answer this: In my experience as an Al Data Trainer and Evaluator, I focused heavily on Reinforcement Learning from Human Feedback (RLHF). My main responsibility involved benchmarking AI-generated responses against strict rubrics for truthfulness and helpfulness. I actively reviewed model outputs to spot edge cases and model hallucinations, while also categorizing and labeling large datasets to improve the precision of machine learning algorithms. It was highly detail-oriented work where I essentially provided the human logic check to ensure the models were trained on safety, accuracy, and strict adherence to complex instructions.

Not specified

Education

A

Automation & Python Courses: Your ongoing work with Python, n8n, and Apify proves the exact technical agility they want

Degree not specified

Not specified
Not specified