Muhammad R.

Key Skills

Software

No software listed

Top Subject Matter

Trust & Safety / Content Moderation / NLP

Computer Vision / Object Tracking

Top Data Types

Text

Image

Top Task Types

Entity (NER) Classification

Tracking

Classification

Freelancer Overview

Trust & Safety Associate — Urdu (Accenture). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include OpenCV. Education includes Bachelor of Science, University of Haripur (2021). AI-training focus includes data types such as Text and Image and labeling workflows including Entity (NER) Classification, Tracking, and Content Moderation.

Labeling Experience

Trust & Safety Associate - Accenture

TextClassification

As a Trust & Safety Associate, he supported workflows that generate high-quality data and guidelines for machine learning systems used in content moderation. He analyzed behavioral and linguistic patterns to help detect spam, scams, and misinformation and translate findings into model and policy improvements. He coordinated with cross-functional teams to ensure consistent labeling, validation, and human-in-the-loop quality control to strengthen platform safety. • Contributed to data taxonomy and dataset creation for trust & safety and NLP model training/evaluation • Performed pattern analysis on online content to identify harmful or misleading content categories • Collaborated on annotation guidelines, labeling taxonomies, and fairness-focused training data improvements • Supported data validation, annotation quality control, and AI-assisted moderation feedback loops

2025 - 2026

Trust & Safety Associate — Urdu (Accenture)

TextEntity (NER) Classification

Contributed to data annotation and content taxonomy workflows for trust & safety, content moderation, and NLP training pipelines. Participated in analyzing behavioral and linguistic patterns to support detection of spam, scams, and misinformation. Helped define annotation guidelines and labeling taxonomies with accuracy, consistency, and fairness as goals. • Annotated and categorized online content according to trust & safety taxonomy • Supported behavioral/language pattern analysis to refine labeling and model behavior • Assisted with creation/maintenance of annotation guidelines and taxonomy structure • Performed annotation quality control and validation for supervised learning datasets

2025 - 2026

Machine Learning Engineer — Data Prism

ImageTracking

Developed computer vision and deep learning tracking pipelines used to improve person tracking and re-identification in retail environments. Implemented and optimized detection and tracking components for Jetson Nano deployment targets. Tuned hyperparameters to improve tracking accuracy and precision and reduced system latency using GPU optimizations. • Built tracking-by-detection workflows for person tracking and re-identification • Trained/optimized YOLO-based detection and DeepSORT/BYTETrack tracking models • Evaluated model performance and improved metrics via fine-tuning • Optimized inference for lower latency on Jetson Nano

2022 - 2023

Education

Work History