Māris Zonne

Key Skills

Software

Scale AI

Internal/Proprietary Tooling

Label Studio

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Geospatial Tiled Imagery

Image

Text

Video

Top Task Types

Action Recognition

Classification

Cuboid

Data Collection

Entity (NER) Classification

Polygon

Red Teaming

Relationship

Segmentation

Text Generation

Freelancer Overview

I have worked on a variety of projects, including computer vision tasks like object tracking and image segmentation, as well as natural language processing tasks such as transcription, named entity recognition (NER), and adversarial prompt creation for large language models. My background includes quality reviewing and giving feedback to other annotators, ensuring high data quality. I am passionate about making technology more accessible and enjoy contributing to projects that advance AI capabilities.

Labeling Experience

Linguistic annotator

Internal Proprietary ToolingTextEntity Ner ClassificationRelationship

Performed NER tasks and reviewed others annotations on publicly available Latvian texts and books. Created adversarial prompts for a LLM, along with maintaining a blacklist of hateful Latvian words. At the end of our data annotation, I was assigned the role of cleaning the data, and making sure there are no inconsistencies. A lot of my work on the second project involved generating hateful prompts and responses.

Performed NER tasks and reviewed others annotations on publicly available Latvian texts and books. Created adversarial prompts for a LLM, along with maintaining a blacklist of hateful Latvian words. At the end of our data annotation, I was assigned the role of cleaning the data, and making sure there are no inconsistencies. A lot of my work on the second project involved generating hateful prompts and responses.

2023 - 2025

General annotator

Scale AIImageBounding BoxPolygon

During this project, I worked on a diverse variety of projects including image and video annotation. They ranged from simple ones, like classifying whether a car had a defect, to complicated ones like creating key points on a persons pose and identifying their intent. Some of the projects were focused on autonomous vehicles, where I had to segment each pixel of an image with labels.

During this project, I worked on a diverse variety of projects including image and video annotation. They ranged from simple ones, like classifying whether a car had a defect, to complicated ones like creating key points on a persons pose and identifying their intent. Some of the projects were focused on autonomous vehicles, where I had to segment each pixel of an image with labels.

2023 - 2024

Satellite image annotator

Scale AIGeospatial Tiled ImageryBounding BoxPolygon

I worked with satellite video data, annotating cars, crosswalks, and other features. The videos were quite short, around 20 frames and were very high resolution. Each object had to be instanced, and instances had to remain the same throughout each frame. The second phase of the project was annotating images of buildings in Ukraine. Each building had to be assigned a label of how damaged it was. From what I understand this was used for analyzing impact after the conflict.

I worked with satellite video data, annotating cars, crosswalks, and other features. The videos were quite short, around 20 frames and were very high resolution. Each object had to be instanced, and instances had to remain the same throughout each frame. The second phase of the project was annotating images of buildings in Ukraine. Each building had to be assigned a label of how damaged it was. From what I understand this was used for analyzing impact after the conflict.

2022 - 2023

LiDAR Data Annotator

Scale AI3D SensorSegmentationCuboid

The project consisted of 320 frame composite scenes from 8 different LiDAR and RADAR sensors on the autonomous car. I was tasked with creating cuboids for sensor issues, active and inactive objects (cars, peds, etc.) and assigning labels on the turn signals, lights of cars, as well as intent of pedestrians. I had also completed tasks using segmentation, where I had to assign every dot of the point cloud a label.

The project consisted of 320 frame composite scenes from 8 different LiDAR and RADAR sensors on the autonomous car. I was tasked with creating cuboids for sensor issues, active and inactive objects (cars, peds, etc.) and assigning labels on the turn signals, lights of cars, as well as intent of pedestrians. I had also completed tasks using segmentation, where I had to assign every dot of the point cloud a label.

2022 - 2023

Insurance image annotator

Label StudioImagePolygonSegmentation

This was a short-term project in Label Studio involving images of damaged cars. Photos were taken from insurance claims and I had to annotate each body panel and windshield, lamps of the car, assign labels on how damaged they are. The second phase consisted of segmenting images of interiors for damage and dirt.

This was a short-term project in Label Studio involving images of damaged cars. Photos were taken from insurance claims and I had to annotate each body panel and windshield, lamps of the car, assign labels on how damaged they are. The second phase consisted of segmenting images of interiors for damage and dirt.

2022 - 2022

Education

Work History