---
title: "Shinde Aditya - AI Engineer in Hyderabad | Tal"
description: "Meet Shinde Aditya, Results-oriented Machine Learning Enthusiast | AI Engineer | GenAI Systems & Inference Optimization based in Hyderabad. AI stack includes antigravity, hugging face, and langgraph. Explore public work links including github and leetcode."
image: "https://tal.club/meet/shinde-aditya/share-image"
---

# Shinde Aditya on Tal

## Headline

Results\-oriented Machine Learning Enthusiast \| AI Engineer \| GenAI Systems & Inference Optimization

## About

Everything is Real\.

## Location

Hyderabad

## AI stack

antigravity

hugging face

langgraph

mcp

claudecode

githubcopilot

## Work experience

AI Engineer at TechOptima, Aug 2025 \- Apr 2026 · 9 mos, Architected Multimodal Streaming Pipelines: Engineered an interactive, real\-time AI Avatar system utilizing state\-of\-the\-art Speech\-to\-Video \(S2V\) synthesis frameworks and streaming LLM outputs; achieved sub\-250ms audio\-visual synchronization latency for production educational platforms\. Optimized Advanced RAG Implementations: Built and deployed an enterprise\-grade RAG pipeline using LlamaIndex and Pinecone; implemented hybrid search \(sparse/dense\), re\-ranking models \(Cohere\), and metadata filtering, reducing hallucination rates by 35% and improving context retrieval accuracy by 42%\. Designed Agentic Workflows: Developed an asynchronous, multi\-agent AI system using LangChain to automate complex data analysis tasks; integrated tool\-calling loops and self\-correction mechanics, increasing autonomous task completion rates to 94%\. Engineered High\-Throughput API Serving Layers: Built a containerized, asynchronous FastAPI serving layer utilizing Docker and AWS EC2 to handle high\-volume concurrent LLM inference requests; optimized memory allocation and request batching, improving system throughput by 55%\. Automated MLOps & Evaluation Pipelines: Established automated CI/CD deployment tracks via GitHub Actions paired with Weights & Biases for monitoring model drift and response latency, cutting production deployment time from days to minutes\.

Machine Learning Engineer at Conquest Technology Solutions Private Limited, India, Feb 2024 \- Jun 2024 · 5 mos, Built Automated Data & Ingestion Pipelines: Engineered high\-performance ETL data pipelines using Python and SQL to extract, clean, and vectorize massive unstructured datasets, reducing downstream embedding generation latency by 45%\. Deployed Predictive Vision Models: Configured and validated real\-time object detection models using YOLO and OpenCV for spatial monitoring; optimized model edge\-inference layers to maximize frame\-rate stability across consumer\-grade hardware\. Fine\-Tuned Specialized Embeddings: Collaborated with senior engineering teams to fine\-tune domain\-specific sentence embeddings; executed comprehensive hyperparameter optimization routines that scaled semantic search relevance across internal databases\.

## Education

Bachelor of Technology, Data Science, Woxsen University

12, Mathematics and Computer Science, Urbane Junior College

## Public links

- github: https://github\.com/heyshinde
- leetcode: https://leetcode\.com/heyshinde

[View the original profile](https://tal.club/meet/shinde-aditya)

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