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Ram Krishna Tiwari

@ramkrishnatiwari

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ML Developer building production-ready real-world AI systems with GenAI, NLP, and computer vision.

India

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What I'm looking for

I want to work on hard, high-impact ML/GenAI problems and deploy them end-to-end—from data pipelines to production endpoints. I’m excited by systems that combine retrieval, multi-agent reasoning, and fast, reliable inference with clean MLOps.

I’m an ML Developer with hands-on experience building and deploying real AI systems—from data pipelines to live production endpoints. I’ve built multi-agent LLM architectures, NLP pipelines, and computer vision systems from scratch, focused on solving hard problems that actually matter.

In recent work, I delivered a RAG-powered query system for semantic search over large-scale scientific datasets, and I engineered context-aware prompts to translate natural language to SQL for intelligent retrieval. I also built an AI-powered multi-agent contract analysis system using Google ADK to automate clause analysis and compliance checks, and developed a real-time behavior detection pipeline by fine-tuning MobileNetV2 for strong accuracy with low-latency deployment. I’m looking to keep pushing models into dependable, reproducible production workflows using tools like MLflow, Docker, and well-structured APIs.

Experience

Work history, roles, and key accomplishments

Multi-Label Movie Classifier

Movie Genre Classification

Jan 2026 - Feb 2026 (1 month)

Built a multi-label movie genre classification system using Binary Relevance and ML-kNN with TF-IDF text features on an IMDB dataset. Ensured end-to-end reproducibility with MLflow and deployed two inference endpoint variants with confidence scoring, latency monitoring, and Docker-based containerized serving.

Multi Label Classification Binary Relevance K NN TF IDF MLFlow Docker REST APIs

WatchNet Real-Time Detection

WatchNet AI

Sep 2025 - Oct 2025 (1 month)

Fine-tuned MobileNetV2 on a custom dataset of 3,000 labeled images to achieve ~85%+ validation accuracy for real-time behavior detection. Delivered a production-ready pipeline for images, video, and live webcam input with sub-100ms inference latency and validated deployment readiness via cross-environment benchmarking.

Computer Vision MobileNetV2 Fine Tuning OpenCV Benchmarking data preprocessing Image Processing Deployment

RAG Query System Hackathon

Argo Data Platform

Jul 2025 - Aug 2025 (1 month)

Built a RAG pipeline using all-MiniLM-L6-v2 embeddings with FAISS and ChromaDB to enable semantic search over large scientific datasets, achieving ~90% query accuracy. Engineered context-aware prompts for GPT-4 to translate natural language to SQL and retrieve data from PostgreSQL.

Retrieval Augmented Generation (RAG)Sentence Transformers Faiss ChromaDB OpenAI API Prompt Engineering PostgreSQL SQL Machine Learning

Multi-Agent Contract Analysis

AI-Powered Contract Analysis

May 2025 - Jun 2025 (1 month)

Architected a multi-agent LLM system for end-to-end contract review using Google ADK, performing clause analysis and compliance checks across tech, healthcare, and finance without manual intervention. Improved classification and summarization across three contract types by integrating industry-specific instructions and built a root agent for intelligent task routing.

Google ADK Contract Analysis Compliance Summarization