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Sajida Shaik

Sajida Shaik

Expert in working with self driving cars data labelling

India flagNandyal, India
$5.00/hrIntermediateOtherInternal Proprietary Tooling

Key Skills

Software

Other
Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor
Geospatial Tiled ImageryGeospatial Tiled Imagery
VideoVideo

Top Task Types

Bounding BoxBounding Box
Data CollectionData Collection
MappingMapping

Freelancer Overview

An expert in labelling maps for self driving cars for accurately detecting lane boundaries and shapes understanding roads, sidewalks, lane areas with the help of images, videos or LiDAR scans (e.g., front/side/rear camera frames or point clouds) Detail-oriented and tech-savvy Data Annotator with hands-on experience in labeling and curating high-quality datasets for machine learning applications. Currently working at NVIDIA, where I annotate and categorize large volumes of vehicle-based image and video data using tools such as CVAT, Labelbox, and VGG Image Annotator. My work includes object detection, segmentation, and classification, with a strong focus on quality control, annotation consistency, and following strict labeling guidelines. I’ve also worked on DeepMap tool-based projects, labeling high-definition maps for autonomous vehicle data—covering elements like lane boundaries, road types, and traffic signs. Skilled in peer review processes and collaborating with QA and data science teams to refine annotation pipelines and ensure data quality. With a background in both science (B.Sc) and business management (MBA), I bring a unique blend of analytical thinking, strategic execution, and operational efficiency. Passionate about advancing AI by delivering precise, reliable data that improves model performance. Seeking new challenges where I can contribute to machine learning pipelines and continue growing in the AI/automation space.

IntermediateHindiEnglish

Labeling Experience

Process executive

Internal Proprietary ToolingGeospatial Tiled ImageryObject Detection
The primary scope of the project was to generate highly accurate, machine-readable HD maps to support the perception, localization, and path-planning systems of autonomous vehicles. The project aimed to deliver centimeter-level precision in road and infrastructure representation, enabling self-driving cars to interpret their surroundings in real time and make safe, informed driving decisions. Key Areas Covered: Urban & Highway Environments: Mapped complex and varied driving scenarios including city streets, suburban neighborhoods, intersections, roundabouts, and multi-lane highways.

The primary scope of the project was to generate highly accurate, machine-readable HD maps to support the perception, localization, and path-planning systems of autonomous vehicles. The project aimed to deliver centimeter-level precision in road and infrastructure representation, enabling self-driving cars to interpret their surroundings in real time and make safe, informed driving decisions. Key Areas Covered: Urban & Highway Environments: Mapped complex and varied driving scenarios including city streets, suburban neighborhoods, intersections, roundabouts, and multi-lane highways.

2023 - Present

Education

J

JNTU

Master of Business Administration, Strategic Planning & Execution

Master of Business Administration
2020 - 2022
N

Nationtal Degree College

Bachelor of Science, N/A

Bachelor of Science
2016 - 2019

Work History

R

Randstand

process Executive

Pune
2023 - Present