PIYUSH CHAUDHARY
NOIDA
Summary
LLM Engineer & Data Scientist (4 YOE) with expertise in Machine Learning, Deep Learning, NLP, and Large Language Models. Proven record of delivering AI solutions with measurable business impact in Telecom and EdTech domains. Strong SQL expertise for analytics, retrieval pipelines, and optimization. Skilled in full ML lifecycle, from model development to production deployment.
Overview
4
4
years of professional experience
1
1
Certification
Work History
Senior Software Engineer
Tech Mahindra
NOIDA
01.2025 - Current
- Company Overview: Client: AT&T (Telecom Service Provider)
- Built and deployed a RAG-based enterprise chatbot, handling 15K+ daily queries and improving first-response efficiency by 30%.
- Built an LLM-based audio summarization service (FastAPI + ElevenLabs) for AT&T, merging news/Reddit data into real-time audio insights.
- Designed SQL-driven retrieval pipelines, cutting factual errors in customer-facing responses by 35%.
- Client: AT&T (Telecom Service Provider)
Associate Data Scientist
Great Lakes Learning
gurugram
08.2021 - 11.2024
- Developed churn prediction models, helping reduce learner dropout rates by 15%.
- Built deep learning systems for automated assignment evaluation, reducing manual grading effort by 40%.
- Created NLP models for sentiment analysis and semantic search, improving course engagement by 20%.
- Designed and deployed an NLP-based recommendation engine, boosting learner course adoption rates by 18%.
- Developed an adaptive tutoring assistant using LLMs, leading to 25% higher student satisfaction scores.
Education
B.Tech - Mechanical Engineering
GL Bajaj
Noida01.2019
Senior Secondary Education -
J.P International School
Noida01.2014
Skills
- Python and SQL
- Data manipulation with Pandas
- Deep learning frameworks: PyTorch and TensorFlow
- Large language models (LLMs)
- Retrieval-augmented generation (RAG)
- Prompt engineering techniques
- Low-rank adaptation (LoRA) and QLoRA
- Transformers architecture
- LangChain and LangGraph integration
- Hugging Face tools
- Regression, classification, and clustering methods
- Convolutional neural networks (CNN)
- Recurrent neural networks (RNN) including LSTM
- Web scraping with Bright Data
- API development using FastAPI
- Data integration strategies
- Containerization with Docker and Kubernetes
- Machine learning workflows with MLFlow and Kubeflow
- Cloud services: AWS, GCP, Azure
- Data warehousing with Redshift
- Cloud computing: EC2 and S3
Certification
- Introduction to Generative AI – Google Cloud
- Prompt Engineering for Everyone – IBM
- Introduction to AI and Machine Learning – Google Cloud
Timeline
Senior Software Engineer
Tech Mahindra
01.2025 - Current
Associate Data Scientist
Great Lakes Learning
08.2021 - 11.2024
B.Tech - Mechanical Engineering
GL Bajaj
Senior Secondary Education -
J.P International School