Jacques Sean Larita

Key Skills

Software

Remotasks

Scale AI

Other

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Image

Video

Top Task Types

Bounding Box

Point Key Point

Polygon

Prompt Response Writing SFT

Segmentation

Freelancer Overview

I am a skilled data annotator with a strong background in LiDAR data labeling, 3D point cloud processing, and image/video annotation for AI training. With hands-on experience working on projects for autonomous vehicles, gaming, and architecture, I specialize in creating high-quality, accurate data to train machine learning models. My expertise includes bounding boxes, semantic segmentation, and 3D segmentation, ensuring precision in tasks ranging from self-driving car imagery to architectural floor plan measurements. I have worked extensively with platforms such as Remotasks and Outlier, completing complex annotation tasks in a remote environment. My ability to adapt quickly to new tools and workflows has allowed me to contribute to a variety of AI applications, including LLM evaluation and gaming data labeling. With a focus on delivering reliable and accurate labeled data, I’m dedicated to supporting the development of cutting-edge AI systems across multiple industries.

Labeling Experience

AI Data Annotation & LLM Evaluation Projects (Outlier Platform)

Internal Proprietary ToolingTextText GenerationText Summarization

Worked on multiple AI data annotation and evaluation projects through the Outlier platform, focusing on improving large language model performance and alignment. Tasks included reviewing and labeling text data, evaluating LLM-generated responses for correctness, relevance, and instruction-following, and classifying prompts based on defined guidelines. Ensured high-quality annotations by strictly adhering to project instructions, quality rubrics, and consistency standards. Maintained accuracy and attention to detail while handling complex and nuanced language tasks to support model training and evaluation at scale.

Worked on multiple AI data annotation and evaluation projects through the Outlier platform, focusing on improving large language model performance and alignment. Tasks included reviewing and labeling text data, evaluating LLM-generated responses for correctness, relevance, and instruction-following, and classifying prompts based on defined guidelines. Ensured high-quality annotations by strictly adhering to project instructions, quality rubrics, and consistency standards. Maintained accuracy and attention to detail while handling complex and nuanced language tasks to support model training and evaluation at scale.

2023

LiDAR Data Annotation for Autonomous Vehicle Development

Scale AI3D SensorBounding BoxPoint Key Point

I worked on annotating LiDAR data for autonomous vehicle development, focusing on object detection and environmental understanding. My tasks included: Bounding Boxes: Labeling objects like vehicles, pedestrians, and traffic signs in 3D space. Semantic Segmentation: Marking road features such as roads, sidewalks, and buildings. Point Cloud Annotation: Annotating individual points to improve vehicle navigation and perception. I ensured high accuracy and consistency in annotations, adhering to quality standards and collaborating with the team to maintain top-tier data quality.

I worked on annotating LiDAR data for autonomous vehicle development, focusing on object detection and environmental understanding. My tasks included: Bounding Boxes: Labeling objects like vehicles, pedestrians, and traffic signs in 3D space. Semantic Segmentation: Marking road features such as roads, sidewalks, and buildings. Point Cloud Annotation: Annotating individual points to improve vehicle navigation and perception. I ensured high accuracy and consistency in annotations, adhering to quality standards and collaborating with the team to maintain top-tier data quality.

2022

Education

Work History