Sivasubraman U.

Key Skills

Software

Data Annotation Tech

Deep Systems

Mindrift

CVAT

OpenCV AI Kit (OAK)

Clickworker

Appen

CloudFactory

Label Studio

Mercor

Redbrick AI

Scale AI

Snorkel AI

Toloka

Trilldata Technologies

Other

Top Subject Matter

Geospatial AI

Spatial Data Analysis

AI Speech Recognition

Top Data Types

Computer Code Programming

Geospatial Tiled Imagery

Image

Text

Video

Audio

Top Task Types

Bounding Box

Point/Key Point

Land Cover Classification

Data Collection

Action Recognition

Question Answering

Text Generation

Diagnosis

Transcription

Computer Programming/Coding

Function Calling

Prompt + Response Writing (SFT)

Text Summarization

Object Detection

Polyline

Classification

Segmentation

Polygon

Audio Recording

Freelancer Overview

Geospatial Analysis (QGIS) Specialist. Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include QGIS and Other. Education includes Doctor of Philosophy, Michigan Technological University (2019). AI-training focus includes data types such as Geospatial, Tiled Imagery, and Audio and labeling workflows including Evaluation, Rating, and Audio Recording.

Labeling Experience

Data Annotation Specialist

MindriftGeospatial Tiled ImageryBounding BoxPoint/Key Point

Currently engaged in the annotation and labeling of geospatial datasets for AI and machine learning applications. Responsibilities include: Delineating parcel boundaries, land cover types, and georeferenced features using high-resolution satellite and aerial imagery. Performing quality control and validation to ensure dataset accuracy and consistency. Utilizing platforms such as Atlas Capture, Crowdgen, and Mindrift for collaborative labeling workflows. Preparing labeled datasets to train and improve computer vision and remote sensing AI models. Adhering to strict labeling guidelines and maintaining documentation for reproducibility and audit purposes. Key Skills Applied: Geospatial data annotation, GIS mapping, AI/ML dataset preparation, quality assurance, remote sensing.

2025 - 2026

Geospatial Analysis (QGIS) Specialist

I designed and managed geospatial projects with QGIS to facilitate AI training and assessment processes for enhanced spatial reasoning capabilities. My main responsibilities involved validating AI-generated spatial outputs to ensure accuracy, logical consistency, and completeness in geospatial data. I refined geospatial datasets, scripts, and evaluation strategies to contribute to high-quality AI model performance. • Led comprehensive quality analysis of spatial data labeling and annotation outputs • Guided model improvement efforts through precise evaluation of training datasets • Enhanced spatial relationship modeling pipelines supporting AI performance • Contributed to rigorous AI workflow documentation and process refinement

2026 - Present

Data Annotation SPecialist

Data Annotation TechVideoAction Recognition

I engaged in video annotation and evaluation projects for AI and machine learning applications, with a focus on action recognition and video captioning. Responsibilities include: Annotating and captioning video content to identify human actions, objects, and events. Performing quality evaluation of annotations to ensure accuracy and consistency for AI training datasets. Using Data Annotation Tech platforms for efficient labeling, collaborative workflows, and real-time evaluation. Assisting in the preparation of datasets for computer vision and action recognition AI models. Maintaining detailed documentation and adhering to strict annotation guidelines for reproducibility and auditing. Key Skills Applied: Video annotation, action recognition, captioning, AI/ML dataset preparation, quality assurance, evaluation & rating.

2025 - 2025

AI prompt Engeneer

Don't discloseTextQuestion AnsweringText Generation

Engaged in prompt evaluation and engineering for AI language models, focusing on improving output quality and alignment with project objectives. Responsibilities include: Designing, testing, and refining prompts to optimize AI model responses. Evaluating AI outputs for accuracy, relevance, coherence, and adherence to instructions. Using human-in-the-loop workflows to provide feedback for model fine-tuning and performance improvement. Collaborating with AI development teams to identify prompt patterns and enhance overall model behavior. Documenting evaluation results and providing actionable recommendations for prompt optimization. Key Skills Applied: Prompt engineering, AI evaluation, human-in-the-loop AI, NLP, AI model fine-tuning, quality assurance.

2024 - 2024

Data Annotation & AI Evaluation Specialist

Other

I evaluated AI model outputs to identify inconsistencies and errors in enterprise geospatial datasets. My data labeling activities focused on bias detection, error correction, and end-to-end quality assurance for AI reasoning tasks. The work directly contributed to optimizing machine learning model performance and reliability. • Performed structured reviews and feedback for AI geospatial tasks • Validated data consistency and logical result flow • Supported human-in-the-loop feedback workflows and iterative model tuning • Applied best practices in error and anomaly identification in labeled datasets

2022 - 2023

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Education

Work History