Hassan Hammoud

Key Skills

Software

Appen

Clickworker

Data Annotation Tech

Deep Systems

Google Cloud Vertex AI

HiveMind

Humanatic

Labelbox

Mercor

Mighty AI

OneForma

Remotasks

Scale AI

Snorkel AI

Toloka

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Image

Text

Video

Top Label Types

Action Recognition

Audio Recording

Bounding Box

Classification

Computer Programming Coding

Data Collection

Emotion Recognition

Evaluation Rating

Fine Tuning

Mapping

Object Detection

Prompt Response Writing SFT

Question Answering

Red Teaming

Relationship

Segmentation

Text Generation

Text Summarization

Tracking

Transcription

Freelancer Overview

I'm an MBA-graduate, AI developer/prompt engineer, and operations leader with over 10 years of experience supporting data-driven systems across AI training, data operations, content creation, and quality assurance. My hands-on work in AI training data includes large-scale data labeling and annotation, building and enforcing QA workflows, and evaluating model outputs for truthfulness, helpfulness, and harmlessness. I bring a strong behavioral science foundation to AI training, ensuring annotations and evaluations are consistent, unbiased, and aligned with human-centered standards. As a former Team Lead at Outlier AI, I led quality assurance and data optimization efforts on complex AI projects such as Flamingo SRT, Geranium Mambo, Dolphin Genesis, and Ostrich GPT. I audited and refined labeling pipelines, provided actionable feedback to annotators, mentored diverse teams, and used performance insights to improve task accuracy and model reliability. In addition to my technical expertise, my background as a senior content creator with 200+ published works strengthens my ability to evaluate language, intent, and authenticity, which are key skills for producing high-quality AI training data while upholding ethical AI practices.

Labeling Experience

Prompt Engineer

Scale AITextQuestion AnsweringText Generation

The Dolphin Genesis and Ostrich GPT were large-scale AI training initiatives focused on improving large language models through structured evaluation, text generation, and comparative analysis. My work involved prompt engineering, professional and long-form writing, labeling and QA of model outputs, and side-by-side comparisons of LLM responses for accuracy, reasoning quality, truthfulness, helpfulness, and harmlessness. I also supported annotator coaching and feedback loops to ensure consistent, ethical, and high-quality training data contributing to the development and refinement of models such as GPT and Google Gemini.

The Dolphin Genesis and Ostrich GPT were large-scale AI training initiatives focused on improving large language models through structured evaluation, text generation, and comparative analysis. My work involved prompt engineering, professional and long-form writing, labeling and QA of model outputs, and side-by-side comparisons of LLM responses for accuracy, reasoning quality, truthfulness, helpfulness, and harmlessness. I also supported annotator coaching and feedback loops to ensure consistent, ethical, and high-quality training data contributing to the development and refinement of models such as GPT and Google Gemini.

2023 - 2024

Flamingo SRT

Scale AITextPrompt Response Writing SFT

Flamingo SRT was a large-scale AI training project that I started on Remotasks (before it became Outlier.ai). It focused on evaluating and improving language model responses for accuracy, reasoning quality, and safety. As a Team Lead, I oversaw data labeling and QA workflows, audited model outputs for truthfulness, helpfulness, and harmlessness, and coached annotators to ensure consistently high-quality, ethically aligned training data.

Flamingo SRT was a large-scale AI training project that I started on Remotasks (before it became Outlier.ai). It focused on evaluating and improving language model responses for accuracy, reasoning quality, and safety. As a Team Lead, I oversaw data labeling and QA workflows, audited model outputs for truthfulness, helpfulness, and harmlessness, and coached annotators to ensure consistently high-quality, ethically aligned training data.

2023 - 2024

Education

Work History