Amani S.

Key Skills

Software

Remotasks

Mindrift

Surge AI

Top Subject Matter

Computer vision and NLP dataset annotation

LLM output evaluation and response quality assurance

Generative AI prompt/task design and content refinement

Top Data Types

Image

Text

Top Task Types

Data Collection

Prompt + Response Writing (SFT)

Fine-tuning

Freelancer Overview

Remotasks — AI Data Annotation Specialist (2021). Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Remotasks, N, and A. Education includes Bachelor of Science, University of California. AI-training focus includes data types such as Image and Text and labeling workflows including Data Collection, Evaluation, and Rating.

Labeling Experience

Surge AI — AI Trainer (2025–Present)

Surge AITextFine-tuning

Develops and evaluates complex AI training tasks derived from real-world workflows. Translates business and technical processes into structured training tasks with clear evaluation criteria. Analyzes model outputs for reasoning accuracy, consistency, and alignment, supporting iterative feedback loops for LLM fine-tuning. • Convert workflows into structured AI training tasks • Create grading rubrics and evaluation criteria • Review outputs for reasoning accuracy and task alignment • Provide iterative feedback to optimize performance

2025 - Present

Mindrift — Generative AI Specialist (2023–2024)

MindriftTextPrompt + Response Writing (SFT)

Designed prompts and realistic task scenarios to improve LLM reasoning and output quality. Rewrote and refined AI-generated content to ensure clarity, coherence, and correctness for downstream use. Created supporting materials, examples, and contextual documents to guide task execution and evaluation. • Authored prompt sets and instruction variations • Refined generated responses for correctness and readability • Produced examples and context to support consistent task delivery • Prepared materials used for guiding evaluation

2023

Invisible — AI Content Evaluator (2022)

Text

Evaluated AI-generated outputs using structured scoring frameworks for accuracy, relevance, and reasoning. Conducted comparative ranking and classification across multiple model responses to determine quality. Flagged hallucinations and logical inconsistencies to support safer, more reliable AI behavior. • Scored outputs using predefined rubric criteria • Ranked and classified responses comparatively • Identified hallucinations and reasoning failures • Reported quality issues based on evaluation results

2022

Remotasks — AI Data Annotation Specialist (2021)

RemotasksImageData Collection

Annotated and structured large-scale datasets for computer vision and NLP use cases, applying detailed labeling guidelines. Ensured training data quality by catching inconsistencies and edge cases. Improved dataset reliability through consistent application of annotation standards across high-volume tasks. • Labeled dataset components per provided instructions • Performed consistency checks to reduce labeling errors • Identified edge cases and ambiguous instances • Contributed to improving overall dataset reliability

2021

Education

Work History