Armin Masoumian

Key Skills

Software

Data Annotation Tech

iMerit

Mercor

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Computer Code Programming

Document

Image

Text

Video

Top Label Types

Action Recognition

Bounding Box

Classification

Computer Programming Coding

Data Collection

Emotion Recognition

Evaluation Rating

Fine Tuning

Object Detection

Prompt Response Writing SFT

Question Answering

Red Teaming

RLHF

Segmentation

Text Generation

Translation Localization

Freelancer Overview

I am a data scientist and machine learning engineer with extensive experience in data annotation, preprocessing, and the development of high-quality AI training datasets, particularly in computer vision and medical imaging domains. My background includes designing and implementing deep learning pipelines for object detection, semantic segmentation, and image classification, where I handled large, complex datasets, performed data cleaning, labeling, normalization, and feature engineering using Python, TensorFlow, PyTorch, OpenCV, and Pandas. I have led projects involving self-supervised learning, built custom data pipelines for healthcare and autonomous vehicle applications, and collaborated closely with cross-functional teams to ensure accuracy and integrity in labeled data. My work has contributed to real-time image enhancement, anomaly detection, and medical diagnosis, and I am passionate about building robust datasets that power reliable AI systems.

Labeling Experience

Subject Expert

MercorTextComputer Programming CodingPrompt Response Writing SFT

Served as a Subject Matter Expert on an LLM evaluation and instruction-tuning project involving high-quality text data, focusing on computer programming and prompt-response writing for supervised fine-tuning (SFT). Reviewed and produced technically accurate prompt–response pairs, evaluated model outputs for correctness, reasoning quality, and adherence to project rubrics, and provided structured feedback to improve response quality and consistency. Worked within Mercor’s labeling environment to maintain high quality standards across diverse programming and prompt-engineering tasks while supporting reliable data generation for model improvement.

Served as a Subject Matter Expert on an LLM evaluation and instruction-tuning project involving high-quality text data, focusing on computer programming and prompt-response writing for supervised fine-tuning (SFT). Reviewed and produced technically accurate prompt–response pairs, evaluated model outputs for correctness, reasoning quality, and adherence to project rubrics, and provided structured feedback to improve response quality and consistency. Worked within Mercor’s labeling environment to maintain high quality standards across diverse programming and prompt-engineering tasks while supporting reliable data generation for model improvement.

2025 - 2025

Education

Work History