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Hi, I am

Divya Sree Murthy

Based in Bengaluru, India.

I build intelligent AI products across computer vision, NLP, RAG, and generative AI. My focus is on clean design, automation, and scalable systems that reduce manual effort and move smoothly from model development to deployment.

View Projects Resume
Divya Sree Murthy
Open to Work

80%

Manual workload reduced through AI automation systems.

1000+

Offer letters and certificates generated every month.

12K+

Text segments embedded for semantic retrieval workflows.

5+

Interns mentored across AI, ML, DL, and RAG topics.

About Me

I enjoy building AI systems that solve practical problems and hold up in real operating environments, not just notebooks.

What I work on

My work spans model development, backend APIs, deployment workflows, and product-facing AI systems. Recent projects include interview intelligence, retrieval-augmented search, document automation, emotion analysis, and vision-driven generative pipelines.

What I optimize for

I care about measurable impact, scalable architecture, and clean implementation. The strongest outcomes in my work come from pairing practical ML with strong workflow design.

Technical Skills

Tools and frameworks I use across machine learning, deployment, vision, NLP, and generative AI workflows.

Core Stack

Python Scikit-learn TensorFlow PyTorch OpenCV Transformers RAG FAISS FastAPI REST APIs Docker Git

Machine Learning

Supervised learning, feature engineering, model training, evaluation, and predictive workflows.

Computer Vision

CNNs, image and video processing, object detection, emotion analysis, and segmentation with SAM.

NLP and LLMs

Transformers, retrieval-augmented generation, embeddings, and multimodal text understanding.

Deployment

Real-time inference pipelines, FastAPI backends, Dockerized services, and production integration.

Professional Experience

Experience focused on deploying practical AI systems, automation pipelines, and applied machine learning workflows.

Dec 2025 - Present

Bengaluru, Onsite

AI/ML Developer

Reintenspark Technology Private Limited

  • Designed and deployed AI-driven automation workflows that reduced manual processing effort by 80%, improving operational efficiency.
  • Engineered an intelligent email processing pipeline, reducing daily processing time from 3 hours to under 30 minutes using rule-based and ML-driven filtering.
  • Developed a multimodal interview analysis system combining computer vision and speech processing to extract behavioral and emotional insights.
  • Mentored and guided 5+ interns on ML, deep learning, and RAG-based systems, improving team productivity and knowledge sharing.
Oct 2025 - Dec 2025

Bengaluru, Onsite

AI Engineer Intern

NKB Playtech Private Limited

  • Developed computer vision pipelines using PyTorch and OpenCV for video-based analysis tasks.
  • Applied preprocessing and feature engineering techniques to improve model accuracy and robustness.
  • Collaborated on building scalable ML components for integration into production workflows.
May 2024 - Jul 2024

Remote

Artificial Intelligence and Machine Learning Intern

EXCELR (AICTE Approved)

  • Built a CNN-based facial emotion recognition system using the FER-2013 dataset.
  • Improved generalization with augmentation, batch normalization, and dropout.
  • Evaluated model performance using accuracy metrics and confusion matrix analysis.

Featured Projects

A selection of AI systems built around multimodal reasoning, retrieval, predictive analytics, and synthetic media generation.

AI-Based Candidate Analysis System

AI-Based Candidate Analysis System

Multimodal interview evaluation system combining computer vision and NLP to generate transcripts, emotion labels, behavioral insights, and recruiter-facing trust signals.

python Computer Vision NLP Speech-to-Text
VectorIQ RAG

VectorIQ RAG

GitHub

RAG-based intelligent search system using FAISS embeddings and Mistral-7B for high-speed semantic retrieval across 12K+ text segments.

python RAG FAISS Mistral-7B
Heart Disease Prediction System

Heart Disease Prediction System

GitHub

End-to-end predictive ML system trained on clinical datasets, supported by dashboards that reduced analysis time by 30%.

python SVM Decision Trees Logistic Regression ANN Scikit-learn Visualization EDA
Automated Casino

Automated Casino

Computer Vision and generative AI pipeline using SAM and Stable Diffusion to segment components, swap assets, and create 3x to 5x synthetic video variations.

python SAM Stable Diffusion OpenCV
Emotion Recognition System

Emotion Recognition System

GitHub

Deep learning-based facial emotion recognition system using CNN to classify human emotions in real-time. Integrated with computer vision techniques for live webcam-based detection and analysis.

python CNN Computer Vision OpenCV TensorFlow Deep Learning
Diabetes Prediction System

Diabetes Prediction System

GitHub

Machine learning-based healthcare system for predicting diabetes risk using Support Vector Machine (SVM). Focused on data preprocessing, feature scaling, and improving prediction reliability for early diagnosis.

python Machine Learning SVM Scikit-learn Data Preprocessing Classification

Education Background

Strong academic grounding in AI and machine learning, backed by high-performing coursework and project execution.

B.Tech in CSE (Artificial Intelligence and Machine Learning)

Sri Venkateswara College of Engineering, affiliated to JNTUA

2021 - 2025 | 80%

Intermediate (MPC)

Sri Chaitanya Junior College

2019 - 2021 | 94.5%

Professional Certifications

Certifications that support my work in AI, data science, Python, and mathematical foundations for machine learning.

Let's Connect

Open to AI/ML engineering roles, applied AI product work, and opportunities involving multimodal systems, retrieval, and intelligent automation.

Email

divyasree202003@gmail.com

Phone

+91 9121655684

Location

Bengaluru, Karnataka