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Sai Keerthi Doma
@sai_keerthi_doma_9ke50vk09
Graduate Student
Lake Los Angeles, CA, United States
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Member since: Jan 22, 2025GenAI Developer and Machine Learning Engineer with around 5 years of experience in AI/ML, specializing in deploying large language models (LLMs), predictive modelling, and data pipeline optimization. Proven expertise in building GenAI solutions like Boeing’s Automated Flight Manual Assistance and solving business challenges at T-Mobile, Future Retail, and Swift Logistics, BSNL. Holds an MS in Computer Science and Engineering, with strong skills in tools like Hugging Face, TensorFlow, and Scikit-learn.
At Boeing, I developed a GenAI-powered assistant using RAG pipelines with LangChain, Pinecone, and GPT-4 for real-time aviation query resolution. Designed a scalable pipeline for processing flight manuals, stored data on Azure Blob Storage, and optimized embeddings with OpenAI embedding for accurate searches. Automated data updates with Azure Event Grid.
As a Jr. Machine Learning Engineer at T-Mobile, I build and deploy predictive models, including churn prediction and sentiment analysis, using TensorFlow and Scikit-learn. I integrate large datasets from CRM and Hadoop systems through Apache NiFi, and deploy models using AWS SageMaker for real-time analytics. Collaborating with data engineering, I optimize data pipelines, ensuring high data quality and scalability across machine learning workflows.
At Future Retail, I implemented demand forecasting models using ARIMA, optimizing inventory management and enhancing business planning. I developed data visualizations using Power BI to present insights, while also automating data processing with Python. My work involved extensive data integration and statistical modeling in supporting data-driven decision-making and improving business performance.
At Swift Logistics, I developed a route optimization system using Python, integrating real-time traffic and weather data for efficient delivery operations. I created a RESTful API for live route updates, automated data workflows, and optimized algorithms to handle large datasets. This work significantly improved logistical efficiency and operational processes.
At BSNL, I developed a system to automate the extraction of customer details like names, phone numbers, and complaints from emails using spaCy. Extracted emails using the IMAP library, annotated and labelled them with Doccano, and then trained a custom NER model on the labelled data. The model improved efficiency by reducing manual data entry and streamlining customer support processes.