Harshita V.

Key Skills

Software

No software listed

Top Subject Matter

AI annotation quality assurance and data pipeline operations

Generative AI model benchmarking and evaluation

Top Data Types

Text

Computer Code Programming

Top Task Types

Tracking

Freelancer Overview

Operations Associate – AI, Deccan AI (AI operations management and annotation pipeline optimization). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Engineering, Stanley College of Engineering and Technology for Women (2022). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Evaluation, Rating, and Tracking.

Labeling Experience

AI Operations Associate - Deccan AI

Tracking

You served as an Operations Associate for AI, owning day-to-day operations for AI delivery activities. You managed end-to-end workflows and introduced quality control practices to improve the reliability of AI outputs. You used analytics and performance tracking to coordinate execution across technical and business stakeholders. • Directed end-to-end annotation pipeline operations with rigorous quality control • Engineered structured workflow systems and performance tracking dashboards • Coordinated cross-functional stakeholder communication to reduce delivery cycle time • Improved dataset accuracy and strengthened model training reliability through QA frameworks

2026 - Present

Operations Associate – AI, Deccan AI (AI operations management and annotation pipeline optimization)

Text

Directed end-to-end AI annotation pipelines and established rigorous quality control mechanisms to improve dataset accuracy and training reliability. Built structured workflows and performance tracking dashboards to monitor annotation throughput across high-volume AI projects. Integrated stakeholder communication channels to reduce delivery cycle time and standardize execution across technical and business teams. • Improved dataset accuracy by 37% through enhanced annotation quality control • Increased operational throughput by 31% by optimizing annotation workflows • Reduced delivery cycle time by 22% via cross-functional alignment • Strengthened model training reliability through dataset integrity improvements

2024 - Present

Gen-AI Intern, BITS Pilani Dubai (generative AI evaluation and analysis)

Text

Performed comparative evaluation (benchmarking) of generative AI systems using advanced assessment frameworks for performance precision. Interpreted complex model performance datasets to generate actionable recommendations for AI strategy decisions. Co-authored and published international research, contributing to scholarly analysis within generative AI evaluation domains. • Achieved 27% improvement in benchmarking precision for generative AI systems • Increased decision-making effectiveness by 33% via actionable performance insights • Produced evaluation outcomes used for competitive programming use cases • Published co-authored international journal research on AI evaluation/analysis

2025 - 2025

Education

Work History