Divya S.

Key Skills

Software

No software listed

Top Subject Matter

Computer Vision (video-based applications)

NLP/Computer Vision (facial emotion recognition)

Generative AI automation

Top Data Types

Video

Text

Image

Top Task Types

Object Detection

Emotion Recognition

Text Generation

Freelancer Overview

AI/ML Developer. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include OpenCV, PyTorch, and FastAPI. Education includes Bachelor of Technology, Sri Venkateswara College of Engineering (2025) and Intermediate, Sri Chaitanya Junior College (2021). AI-training focus includes data types such as Video and Text and labeling workflows including Object Detection, Emotion Recognition, and Text Generation.

Labeling Experience

AI/ML Developer — Reintenspark Technology Private Limited (Dec 2025 – June 2026)

TextText Generation

In the role, you led development of AI-driven automation systems that produced structured outputs for downstream use cases, including document generation at scale. You built an automated email pipeline to process and accelerate document-related workflows, which required preparing and validating text inputs/outputs used in automation. You also developed and integrated emotion detection and speech-to-text pipelines that convert multimodal inputs into labeled outputs for analysis. • Document/email automation with text processing • Speech-to-text pipeline integration for analysis • CNN-based emotion detection and integration • Generated 1000+ offer letters & certificates per month

2025 - 2026

AI Engineer Intern — NKB Playtech Private Limited (Oct 2025 – Dec 2025)

VideoObject Detection

In the role, you developed PyTorch and OpenCV-based models for video applications, which required preparing and evaluating video inputs and derived training data. You performed data preprocessing, feature extraction, and model evaluation to improve performance for computer vision tasks on video content. Your work supported building end-to-end ML pipelines that convert raw video into model-ready representations. • Video model development • Data preprocessing and feature extraction • Model evaluation and performance improvement • Computer vision pipeline optimization

2025 - 2025

Artificial Intelligence and Machine Learning Intern — EXCELR (May 2024 – July 2024)

VideoEmotion Recognition

In the role, you built a CNN-based facial emotion recognition system using the FER-2013 dataset. You improved model generalization by applying augmentation and regularization techniques such as Batch Normalization and Dropout. Your training work focused on learning robust emotion labels from face images and evaluating the resulting model behavior for emotion classification. • Facial emotion recognition model development • Dataset-based training for emotion labels • Augmentation for generalization • Regularization using Batch Normalization and Dropout

2024 - 2024

Education

Work History