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I'm an AI/ML Engineer with 5 years of experience designing, developing, and deploying scalable machine learning systems, including generative AI solutions and cloud-native data platforms. I enjoy turning complex data problems into robust, maintainable, and impactful solutions that help teams move faster. I excel at building end-to-end ML pipelines across AWS and Azure, collaborating with cross-functional teams to translate technical requirements into clear, actionable plans. I stay curious, keep learning, and value clean code, strong governance, and trustworthy AI systems.…I'm an AI/ML Engineer with 5 years of experience designing, developing, and deploying scalable machine learning systems, including generative AI solutions and cloud-native data platforms. I enjoy turning complex data problems into robust, maintainable, and impactful solutions that help teams move faster. I excel at building end-to-end ML pipelines across AWS and Azure, collaborating with cross-functional teams to translate technical requirements into clear, actionable plans. I stay curious, keep learning, and value clean code, strong governance, and trustworthy AI systems.

Rasi Elluri

AI Engineer, Data Scientist, Full Stack Developer, +2

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I'm an AI/ML Engineer with 5 years of experience designing, developing, and deploying scalable machine learning systems, including generative AI solutions and cloud-native data platforms. I enjoy turning complex data problems into robust, maintainable, and impactful solutions that help teams move faster. I excel at building end-to-end ML pipelines across AWS and Azure, collaborating with cross-functional teams to translate technical requirements into clear, actionable plans. I stay curious, keep learning, and value clean code, strong governance, and trustworthy AI systems.…I'm an AI/ML Engineer with 5 years of experience designing, developing, and deploying scalable machine learning systems, including generative AI solutions and cloud-native data platforms. I enjoy turning complex data problems into robust, maintainable, and impactful solutions that help teams move faster. I excel at building end-to-end ML pipelines across AWS and Azure, collaborating with cross-functional teams to translate technical requirements into clear, actionable plans. I stay curious, keep learning, and value clean code, strong governance, and trustworthy AI systems.

Available to hire

I’m an AI/ML Engineer with 5 years of experience designing, developing, and deploying scalable machine learning systems, including generative AI solutions and cloud-native data platforms. I enjoy turning complex data problems into robust, maintainable, and impactful solutions that help teams move faster.

I excel at building end-to-end ML pipelines across AWS and Azure, collaborating with cross-functional teams to translate technical requirements into clear, actionable plans. I stay curious, keep learning, and value clean code, strong governance, and trustworthy AI systems.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at Shrive Solutions LLC

August 1, 2023 - December 1, 2023

Architected and delivered production-grade AI systems using RAG and genetic architectures, achieving 100% verifiable legal citations by integrating knowledge graphs, vector databases, and multi-LLM orchestration. Led deployment of agent capabilities through LangGraph and Auto Gen, coordinating GPT-4 and Claude 3.5 Sonnnet models for reasoning, drafting, validation, and iterative refinement of complex legal drafting tasks.

Data Scientist at Shrive Solutions LLC

August 1, 2023 - December 1, 2023

Assisted in developing predictive analytics models using XGBoost and scikit-learn to forecast sales demand across multiple product categories, contributing to a 22% improvement in forecast accuracy across varied market segments.

Data Engineer at VMware

September 1, 2019 - May 1, 2022

Designed and developed scalable ETL pipelines using Apache Spark and PyTorch to process large-scale structured and unstructured data sets, reducing end-to-end data processing time by 35% for global reporting systems. Optimized SQL queries and data models in Snowflake and Amazon Redshift through indexing, clustering, and partitioning to improve query speed and reduce compute costs by 20%. Automated ingestion of diverse data sources (REST APIs, flat files, streaming feeds) into centralized cloud-based data warehouses, ensuring timely, reliable data for analytics teams. Built robust data quality validation frameworks with PySpark and SQL to monitor and resolve data issues, achieving over 98% accuracy across critical enterprise data sets. Implemented incremental load and CDC processes in Apache Airflow to streamline data refresh cycles and minimize pipeline failures in production environments. Collaborated with cross-functional teams to migrate legacy ETL workflows to modern cloud-native a