Saketh Reddy Email & Phone Number

Bengaluru, Ka, In

Bengaluru, Karnataka, India

->End-to-End MLOps Implementation: Developed and deployed MLOps pipelines in Azure Machine Learning, encompassing data ingestion, preprocessing, model development using the Scikit-learn framework, REST API creation for model inferencing, and ongoing model and data drift monitoring.->Model Deployment Automation: Automated the deployment process of machine learning models from AWS SageMaker to Hugging Face utilizing AWS Lambda functions, enhancing deployment efficiency and scalability.->RAG Applications Development: Designed and implemented Retrieval-Augmented Generation (RAG) applications within Copilot and AI Studio to address diverse business use cases, optimizing information retrieval and enhancing model performance.->Synthetic Data Generation Tool: Created a synthetic data generation tool leveraging Mistral AI and OpenAI, utilizing the Langchain framework to produce high-quality synthetic datasets for model training and validation.

Bengaluru, Karnataka, India

-> Worked as a backend developer in Phoenix team which creates a common platform for multiple tenants of Zebra to communicate in a fast and efficient way. -> I have worked on development of microservices, Oauth integration and writing Junit test cases for the platform using Java, Spring Boot, MongoDB, REST API and gRPC technologies.

India

-> Worked as frontend developer in Implementation of UI using React JS-> Built functionalities like history section that keeps track of changes for better tracking of projects and tasks happening in KaizIQ SDLC tool. -> Created unit test cases, fixed bugs and assisted in planning discussions.

Bengaluru, Karnataka, India

-> Developed a model to test the performance of a dataset by resampling it using augmentation techniques.-> Incorporated 7 different augmentation techniques into the working model using the nlpaug library to perform sentence and word-level augmentation.-> The model is tested against different benchmark datasets like tweet dataset to classify tweets and with an Easy-VQA dataset to test the performance of model in question-answering tasks.-> The model gave 1–3% more accuracy in the QA task after the augmentation of a dataset.

Bachelor Of Engineering - Be, Computer Science And Engineering, 9.21/10

Class 12Th, 9.94/10

Class - 10Th, 9.8/10