Manjiri Kawathe

Designed and deployed an Agentic AI Solution for DVLA logistics using Langgraph and OpenAI LLMs on Azure, implementing a RAG architecture with Pinecone and ADA 002 embeddings. Developed a conversational shopping assistant for ASDA using RAG and LLMs, deploying solutions with Docker/EKS and establishing Model Drift Monitoring. Productionized code with Python 3.7/PyTest and deployed models using Azu

Developed Deep Learning and XGBoost models for housing tax assessment error identification, deploying the system as a micro-service using EKS and integrating into MLops workflows. Conducted extensive EDA, implemented data pipelines, performed clustering and segmentation analysis, and experimented with various classification methods. Managed development activities using Agile, Control-M, UNIX, Pyth

Prepared data science models for deployment and lifetime management for HSBC, setting up CI/CD pipelines using Jenkins and Azure Dev-Ops and configuring training/inference/re-training pipelines. Established model monitoring and drift mitigation strategies within Azure ecosystems, and led solution design using AWS Batch and Docker Containers. Deployed models as Python APIs using Flask/Fast API with

Performed analysis and evaluation of customer requirements for RENAULT projects, designing and developing new applications and modifying DataStage jobs with strong SQL skills. Used Hyperion Essbase and Linux for data processing and billing calculations, implemented business logic in Shell Scripting, and analyzed/resolved issues. Participated in Scrum calls, attended client meetings, and supported

Grade: Merit

Activities and societies: Relevant Coursework: Machine Learning, Deep Learning Theory, Big Data Tools and Techniques, Distributed Information Systems, Advanced Topics in Software Engineering, Computer vision.

Pursued a Master's degree focusing on advanced topics in computer science and data science. Studied relevant coursework including Machine Learning, Deep Learning Theory, Big Data Tools and Techniques, and Distributed Information Systems. Achieved a Merit grade.

Completed a Bachelor of Engineering degree with a specialization in Computer Science Engineering. Gained foundational knowledge and skills in computer science principles and practices.