# Peter Kigen

Peter Kigen is a remote worker on Himalayas, AI Data Annotation & Evaluation Specialist at Unknown, based in Kenya.

Source: https://himalayas.app/@peterkigen

```text
AI Evaluation Specialist performing RLHF response ranking and reviewing language-model training data.
```

| Detail | Value |
| --- | --- |
| Availability | Looking for a job |
| Location | Kenya |
| Authorized to work in | Kenya |
| Salary expectations | 60k+ USD |
| Job categories | AI Analyst, AI Evaluator, Data Annotator, Content Quality Reviewer |
| Skills | AI Evaluation, RLHF Preference Ranking, Response Rating, Response Scoring (Utility), Data Annotation, Data Labeling, Content Review, Quality Calibration, Rubric based Evaluation, Red Teaming, Large Language Models, Supervised FineTuning, Machine Learning, Natural Language Processing, Text Classification |

## What I'm looking for

```text
I’m seeking AI Evaluation / AI Training Analyst opportunities where I can contribute high-quality human feedback to frontier model development. I’m open to domain-specific evaluation across general AI, STEM reasoning, business, legal, and multilingual tasks.
```

## About

```text
In my current AI Data Annotation & Evaluation Specialist role, I annotate and review large language model training data across general knowledge, reasoning, and safety domains. I’ve completed 8,000+ annotation and evaluation tasks.

I rank model responses using RLHF-style evaluation and write evidence-based justifications against accuracy, helpfulness, coherence, and safety criteria. I also flag edge cases and ambiguities that contribute to improvements in evaluation rubrics.

At Scale AI, I reviewed AI-generated text for factual accuracy, relevance, tone, and policy compliance in RLHF and supervised fine-tuning data pipelines. I provided structured feedback for preference models and achieved top-quartile quality metrics during my internship.

My capstone at United States International University – Africa involved developing and evaluating a multi-turn conversational AI agent focused on factual accuracy and safety alignment. I ranked responses and conducted preference modeling across 1,200+ generated outputs.
```

## Experience

### AI Data Annotation & Evaluation Specialist (current)

Unknown. Jan 2024 - Present

```text
Performed high-volume data annotation, content labeling, and quality review for large language model training datasets. Conducted preference ranking (RLHF-style) of model responses and maintained consistent quality scores above platform averages.
```

Skills: Data-Annotation, Content-Labeling, Quality-Review, RLHF, Preference-Ranking, Evaluation, Attention-To-Detail, response-evaluation, Safety-Domains, Guideline-Adherence, Calibration-Sets

### Data Annotation Specialist

Various AI Data Platforms. Jan 2023 - Jan 2024

```text
Executed text classification, entity recognition, sentiment analysis, and content moderation tasks for computer vision and NLP model training. Built strong foundation in following precise labeling guidelines and delivering consistent, high-accuracy annotations under volume targets.
```

Skills: Text-Classification, Named-Entity-Recognition, Sentiment-Analysis, Content-Moderation, Data-Annotation, Data-Labeling, Guideline-Adherence, Accuracy

### AI Content Review Intern

[Scale AI](https://himalayas.app/companies/scale). Jun 2023 - Dec 2023

```text
Reviewed and rated AI-generated text for factual accuracy, relevance, tone, and policy compliance as part of large-scale RLHF and supervised fine-tuning data pipelines. Applied complex multi-dimensional rubrics to score responses and provided structured written feedback.
```

Skills: Content-Review, RLHF, Data-Annotation, Quality-Assurance, Written-Communication, Response-Rating, Supervised-FineTuning, Rubric-Application, Written-feedback, Attention-To-Detail

## Education

### United States International University – Africa (USIU-Africa)

Bachelor of Science, Artificial Intelligence

Activities and societies: Capstone Project: Developed and evaluated a multi-turn conversational AI agent focused on factual accuracy and safety alignment; conducted systematic response ranking and preference modeling (RLHF-style evaluation) across 1,200+ generated outputs.

```text
Bachelor of Science in Artificial Intelligence with relevant coursework in machine learning, natural language processing, AI ethics and safety, data mining, human-computer interaction, and statistical analysis. Capstone project involved developing and evaluating a multi-turn conversational AI agent focused on factual accuracy and safety alignment.
```

## Tech stack

- Google Workspace
- Microsoft Excel
- Microsoft PowerPoint

To contact Peter, message them from this profile with a Himalayas employer account: [Hire on Himalayas](https://himalayas.app/hire).

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