Weisheng Jin

Key Skills

Software

Appen

Clickworker

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Audio Recording

Bounding Box

Classification

Data Collection

Entity Ner Classification

Freelancer Overview

Overview: Proficient in data labeling for AI training, delivering high-quality, accurate datasets critical for machine learning models across domains like autonomous driving, NLP, and computer vision. Key Skills: Precision Annotation: Expertise in tools like Labelbox and Prodigy for tasks such as bounding box creation, semantic segmentation, and text annotation. Domain Adaptability: Experience with diverse datasets, including LiDAR for autonomous vehicles, medical imaging, and multilingual text for NLP. Quality Control: Skilled in cross-validation and inter-annotator agreement to ensure dataset consistency and reliability. Automation: Proficient in Python scripting to streamline labeling workflows and align with ML model requirements. Project Highlights: Contributed to large-scale projects, such as annotating sensor data for self-driving cars and semantic analysis for chatbot training. Impact: My meticulous approach and domain-specific knowledge enable robust, scalable AI solutions, ensuring models achieve high performance and accuracy.

Labeling Experience

text labelling

ClickworkerTextText GenerationText Summarization

The AI Trainer for Autonomous Vehicles project focuses on developing and refining artificial intelligence models to enhance self-driving car performance. The role involves collecting, annotating, and curating high-quality datasets from sensors like LiDAR, cameras, and radar. Trainers design and implement machine learning algorithms to improve perception, decision-making, and navigation in complex environments. The project emphasizes real-time data processing, safety optimization, and ethical AI practices. Collaboration with engineers ensures seamless integration into vehicle systems. The goal is to create robust, reliable AI that enables safe, efficient autonomous driving across diverse scenarios.

The AI Trainer for Autonomous Vehicles project focuses on developing and refining artificial intelligence models to enhance self-driving car performance. The role involves collecting, annotating, and curating high-quality datasets from sensors like LiDAR, cameras, and radar. Trainers design and implement machine learning algorithms to improve perception, decision-making, and navigation in complex environments. The project emphasizes real-time data processing, safety optimization, and ethical AI practices. Collaboration with engineers ensures seamless integration into vehicle systems. The goal is to create robust, reliable AI that enables safe, efficient autonomous driving across diverse scenarios.

2023 - 2023

Education

Work History