Swathi Mohan

Data Annotation and Data Review professional with 3+ years of experience in computer vision annotation, supporting Autonomous Vehicle (AV), ADAS, and robotics projects. Experienced in semantic segmentation, object detection, lane detection, polyline detection, 2D/3D bounding boxes, and LiDAR annotation. Skilled in maintaining annotation accuracy, performing quality checks, meeting client deadlines, and working with multiple annotation platforms including UAI, Playment, YAM, LabelMe, and Supervisely.

DATA ASSOCIATE at L&T TECHNOLOGY SERVICES (2019-04 – 2020-08)

Worked as a Data Associate in the data annotation domain, supporting Autonomous Vehicle (AV) and Advanced Driver Assistance Systems (ADAS) projects.

• Performed semantic segmentation for self-driving vehicle datasets.
• Worked on semantic segmentation, lane detection, object detection, polyline detection, and LiDAR annotation using 2D and 3D bounding boxes.
• Ensured high-quality annotations while consistently meeting client-defined deadlines and quality requirements.
• Performed quality checks and maintained annotation accuracy according to project guidelines.
• Worked with multiple annotation platforms and tools for autonomous driving projects.
• Tools: UAI, Playment, YAM.

DATA ANNOTATOR INTERN at KOIREADER TECHNOLOGIES (2024-10 – 2026-08)

Worked as a Data Annotator Intern in the computer vision and data annotation domain.

• Performed semantic segmentation on image datasets according to project-specific annotation guidelines.
• Maintained annotation accuracy and quality while meeting project deadlines.
• Performed quality checks to ensure annotations met client and project requirements.
• Worked with annotation tools for computer vision and autonomous driving-related projects.
• Tool: LabelMe.

DATA REVIEWER / SENIOR ANNOTATOR at CLUTTERBOT TECHNOLOGIES PRIVATE LIMITED (2025-10 – Present)

Working as a Data Reviewer / Senior Data Annotator in the computer vision and robotics data annotation domain.

• Working on semantic segmentation and 2D bounding box annotation.
• Reviewing annotations for accuracy, consistency, and compliance with project guidelines.
• Performing quality checks and identifying annotation errors to maintain dataset quality.
• Meeting project deadlines while maintaining required quality standards.
• Working with annotation platforms used for robotics and computer vision datasets.
• Tool: Supervisely.

Master in computer applications in Computer applications – MIT (2017)

Bachelor of computer application in Computer application – MMK & SDM (2014)

Pre University Education – SDM (2011)

SSLC – Ideal Jawa Rotary High School (2009)