Sreehari Pradeep Kumar

MSc in Data Science

September 2021 - July 2024

• Advance Text Analytics
• Deep Learning
• High Level Computer Vision
• Generative AI
• Advance Software Engineering

B.Tech. in Electornics and Communication Engineering

August 2014 - August 2018

• C Programming
• Embedded Systems
• ApplicationsofMicrocontroller & Microprocessor

Self Employed

January 2025 - Present

Fellow

• Developed an end to end MVP Multi Agent app for Trade & Logistics on multilingual commodity emails and docs.
• The app utilized multi-agent doc parser and hybrid RAG (graph + vector) pipeline powering a multilingual chatbot.
• Agentic AI applications for real‑world use case with STT and TTS models
• Founding AI Team member of Sartech Labs.

EuroTech federation

June 2025 - Present

Fellow

• Developed an end to end MVP Multi Agent app for Trade & Logistics on multilingual commodity emails and docs.
• The app utilized multi-agent doc parser and hybrid RAG (graph + vector) pipeline powering a multilingual chatbot.
• Agentic AI applications for real‑world use case with STT and TTS models
• Conducted learning sessions on LLMs, Multi‑Agent Systems using N8N, AutoGen, CrewAI, and Python, reaching over 2,500+ participants.

DPS-UnternehmerTUM

September 2024 - December 2024

AI Engineer

• Developed a multi-agent RAG tool called KIRK (KI-Rotes Kreuz) for Deutsches Rotes Kreuz Baden-Württemberg
• Used Groq (LPU), Crew AI multi-agents for LLM guard rails, table parsing
• Handled over to over 1000+ docs with Langchain, Qdrant as vector DB and Postgresql for Chat
• RAG evaluation using RAGAs framework and user testing
• App dockerized with CI/CD and deployment using Coolify-Git

ZEW & Philipps-University Marburg

June 2023 - September 2024

NLP Engineer, Student Assistant

• Boiler plate detection of German Privacy Policies Pre and Post GDPR using longformer-transformer and doc similarity
• Parameter Efficient Fine Tuning of LLM using together ai
• Built and automated pipeline for data scraping, cleaning, preprocessing and transformating of over 7.5M privacy policies
• Named Entity Recognition (NER) on 7.5M German and US privacy policies using spacy-transformer
• Productive scraping of 7.5M privacy docs with AWS orchestration & SQL-BigQuery analysis for 662K firms under 2 months.

Würth Group

September 2022 - March 2023

Data Science, Working Student

• Improved customer buying prediction accuracy for 1.5M customers with XGBoost, Ensemble models and neural networks within 3 months.
• Elevated stakeholder insights with interactive visualization tool for customer segmentation using PCA & Autoencoder in 2 months.
• Optimized ML pipelines for business use cases, enhancing processing speed by 80% within 2 months.

Würth Group

July 2022 - September 2022

Data Science Intern

• Built and evaluated Recommendation System with 75% accuracy using pyspark and deep neural networks in over 2 months.
• Engineered ML pipelines for data integration to deployment for recommendation system in 4 weeks.
• Large scale data analysis using Apache SPARK, SQL and Scikit-learn for cross selling analysis

Tata Consultancy Services

November 2018 - August 2021

Systems Engineer

• Aligned with over 4+ technical and non‑technical stakeholders for requirement and PoCs
• Accelerated deployment by 50% with CI/CD pipelines and model monitoring
• Automated an outstanding financial amount computing system for IFRS9
• Developed and reduced testing time by 90% with automation scripts using Selenium and Java
• Leveraged SQL to extract over 1 million data points from databases

Software Associates

July 2018 - October 2018

Machine Learning Intern

• Developed a Hand Gesture Recognition System on ESP 32 with Accelerometer.
• Used Micropython and Embedded C to program ESP 32.
• Implemented ensemble model for prediction and WEKA for analysis.

Languages and Databases

Frameworks

Tools