Joseph James

Key Skills

Software

Sama

Remotasks

Scale AI

Other

Appen

Top Subject Matter

Legal Services & Contract Review

Regulatory Compliance & Risk Analysis

Legal Research & Document Analysis

Top Data Types

Image

Text

Document

Video

3D Sensor

Top Task Types

Segmentation

Cuboid

Classification

Bounding Box

Tracking

Point Key Point

Freelancer Overview

Freelance AI Consultant in Contract Review, Compliance, and Legal Research. Brings 6+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Well suited for text-focused AI training, including legal document review, compliance annotation, and rubric-based quality evaluation.

Labeling Experience

Senior Data Labeling Specialist - Sama (Human-Centered AI)

SamaVideoSegmentationTracking

As a Senior Data Labeling Specialist at Sama, I performed high-volume annotation for computer vision models, focusing on autonomous vehicle datasets. My responsibilities included detailed image labeling using bounding boxes and semantic segmentation to identify objects and ensure temporal consistency across video frames. I reviewed annotations for quality, maintained high accuracy standards, and trained junior annotators. • Consistently labeled 1,500+ images weekly for machine learning model training. • Utilized Labelbox and proprietary Sama tools for polygons, semantic segmentation, and 3D cuboids. • Flagged challenging edge cases and contributed to guidelines. • Achieved a team-wide accuracy rate above 97%.

As a Senior Data Labeling Specialist at Sama, I performed high-volume annotation for computer vision models, focusing on autonomous vehicle datasets. My responsibilities included detailed image labeling using bounding boxes and semantic segmentation to identify objects and ensure temporal consistency across video frames. I reviewed annotations for quality, maintained high accuracy standards, and trained junior annotators. • Consistently labeled 1,500+ images weekly for machine learning model training. • Utilized Labelbox and proprietary Sama tools for polygons, semantic segmentation, and 3D cuboids. • Flagged challenging edge cases and contributed to guidelines. • Achieved a team-wide accuracy rate above 97%.

2022 - Present

Project Labeler - E-commerce Product Image Tagging (Appen)

AppenImageClassification

On the E-commerce Product Image Tagging project with Appen, I provided metadata and attribute tags for thousands of product images. My work involved detailed classification of colors, patterns, and styles to aid automated inventory systems. This helped support computer vision models in product categorization. • Labeled 5,000+ product images for a global client. • Used Appen's annotation tools for attribute tagging. • Focused on quality control for repeated categories and edge cases. • Improved accuracy of automated e-commerce inventory systems.

On the E-commerce Product Image Tagging project with Appen, I provided metadata and attribute tags for thousands of product images. My work involved detailed classification of colors, patterns, and styles to aid automated inventory systems. This helped support computer vision models in product categorization. • Labeled 5,000+ product images for a global client. • Used Appen's annotation tools for attribute tagging. • Focused on quality control for repeated categories and edge cases. • Improved accuracy of automated e-commerce inventory systems.

2021 - 2021

Data Annotator (Text Tasks) - Remotasks, Scale AI

Scale AI3D SensorClassificationCuboid

During my time at Remotasks and Scale AI, I performed 3D cuboid annotation in LiDAR point clouds for robotics and self-driving car projects. I labeled thousands of objects across point cloud frames, ensuring accurate object boundaries in 3D space. This work strengthened the object detection and tracking capabilities of ML models for autonomous navigation. • Labeled 3D sensor data for self-driving vehicle use cases. • Used specialized interface in Scale AI for efficient cuboid drawing. • Achieved consistently high quality via rigorous guideline adherence. • Contributed to LiDAR dataset growth across several projects.

During my time at Remotasks and Scale AI, I performed 3D cuboid annotation in LiDAR point clouds for robotics and self-driving car projects. I labeled thousands of objects across point cloud frames, ensuring accurate object boundaries in 3D space. This work strengthened the object detection and tracking capabilities of ML models for autonomous navigation. • Labeled 3D sensor data for self-driving vehicle use cases. • Used specialized interface in Scale AI for efficient cuboid drawing. • Achieved consistently high quality via rigorous guideline adherence. • Contributed to LiDAR dataset growth across several projects.

2020 - 2021

Data Annotator (Image & Video) - Remotasks, Scale AI

Scale AIImageCuboidPoint Key Point

At Remotasks and Scale AI, I specialized in labeling 2D images and performing 3D cuboid annotation for LiDAR point cloud data. My work supported AI and robotics models with keypoint labeling for human pose estimation and object detection. I followed precise instructions and maximized throughput without sacrificing quality. • Labeled images and LiDAR frames for autonomous driving and robotics. • Annotated key points for pose estimation and objects in 3D space. • Handled multi-modal data and diverse annotation projects. • Developed workflow enhancements to improve labeling speed by 20%.

At Remotasks and Scale AI, I specialized in labeling 2D images and performing 3D cuboid annotation for LiDAR point cloud data. My work supported AI and robotics models with keypoint labeling for human pose estimation and object detection. I followed precise instructions and maximized throughput without sacrificing quality. • Labeled images and LiDAR frames for autonomous driving and robotics. • Annotated key points for pose estimation and objects in 3D space. • Handled multi-modal data and diverse annotation projects. • Developed workflow enhancements to improve labeling speed by 20%.

2020 - 2021

Trainee - Medical Image Segmentation Simulation

OtherSegmentation

During a medical image segmentation training simulation, I practiced segmenting anatomical structures in X-ray and MRI images. This module emphasized accuracy and confidentiality when handling sensitive health data for AI model training. I gained competency in medical image annotation necessary for healthcare AI dataset creation. • Segmented anatomical regions in medical images for training. • Maintained strict privacy protocols throughout annotation exercises. • Followed best practices for medical labeling and data access. • Achieved full completion of the simulation with high precision.

During a medical image segmentation training simulation, I practiced segmenting anatomical structures in X-ray and MRI images. This module emphasized accuracy and confidentiality when handling sensitive health data for AI model training. I gained competency in medical image annotation necessary for healthcare AI dataset creation. • Segmented anatomical regions in medical images for training. • Maintained strict privacy protocols throughout annotation exercises. • Followed best practices for medical labeling and data access. • Achieved full completion of the simulation with high precision.

2020 - 2020

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Education

Work History