Puttatida M.

I'm an ML/AI Research Engineer from the UK (5 years of experience) previously worked with Carnegie Learning, NetAI, and EEDI. I specialise in deep learning, NLP, LLMs, RAG/GraphRAG, Graph neural network, and agentic AI. I hold MSc Machine Learning from Queen Mary University of London. I am proficient with a modern ML/LLM stack including Pandas, NumPy, PyTorch, Hugging Face Transformers, LangChain, LangGraph, LlamaIndex, and CrewAI for agentic workflows, alongside frameworks like Microsoft GraphRAG and LightRAG. I work across the current vector database (Chroma, Pinecone, pgvector) and use Neo4j with Cypher for knowledge graphs. My research interests are LLM evaluation (Arize Phoenix) and mechanistic interpretability. I have extensive experience with AWS (SageMaker, Bedrock, Lambda, CloudFormation, CloudWatch, Lex, RDS), good SQL skills, and a solid grounding in MLOps. Im proficient from research and development to deployment in production environments. I also specialised in building any deep learning architecture from scratch with full understanding of the theory/mathematical nuance beneath, including GNN and computer vision systems, as well as LLM. I have done forecasting work across different domains (education, healthcare, network optimisation) I have a grounded knowledge in advanced statistics (probability theory, Distributions, Bayesian Inference) and have substantial experience in the Data Science domain (Explanatory Data Analysis, Data Visualisation) and Data engineering and had previous experience automating the whole pre-processing pipeline for machine learning.