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I’m Budhilsai Kosireddi, an AI/ML Engineer with a focus on building scalable machine learning models, generative AI applications, and retrieval-augmented generation (RAG) solutions across conversational AI, document intelligence, and workflow automation domains. I thrive in cross-functional teams and enjoy turning complex problems into practical, production-ready AI solutions that empower researchers and engineers alike. I’m proficient in Python, PyTorch, TensorFlow, LangChain, FAISS, and FastAPI, with hands-on experience deploying scalable AI services and end-to-end ML solutions. I also excel at refining prompts, designing evaluation pipelines for large language model use cases, and streamlining data ingestion and embedding workflows to boost retrieval accuracy and user experiences in production environments.…I’m Budhilsai Kosireddi, an AI/ML Engineer with a focus on building scalable machine learning models, generative AI applications, and retrieval-augmented generation (RAG) solutions across conversational AI, document intelligence, and workflow automation domains. I thrive in cross-functional teams and enjoy turning complex problems into practical, production-ready AI solutions that empower researchers and engineers alike. I’m proficient in Python, PyTorch, TensorFlow, LangChain, FAISS, and FastAPI, with hands-on experience deploying scalable AI services and end-to-end ML solutions. I also excel at refining prompts, designing evaluation pipelines for large language model use cases, and streamlining data ingestion and embedding workflows to boost retrieval accuracy and user experiences in production environments.

Budhilsai Kosireddi

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

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I’m Budhilsai Kosireddi, an AI/ML Engineer with a focus on building scalable machine learning models, generative AI applications, and retrieval-augmented generation (RAG) solutions across conversational AI, document intelligence, and workflow automation domains. I thrive in cross-functional teams and enjoy turning complex problems into practical, production-ready AI solutions that empower researchers and engineers alike. I’m proficient in Python, PyTorch, TensorFlow, LangChain, FAISS, and FastAPI, with hands-on experience deploying scalable AI services and end-to-end ML solutions. I also excel at refining prompts, designing evaluation pipelines for large language model use cases, and streamlining data ingestion and embedding workflows to boost retrieval accuracy and user experiences in production environments.…I’m Budhilsai Kosireddi, an AI/ML Engineer with a focus on building scalable machine learning models, generative AI applications, and retrieval-augmented generation (RAG) solutions across conversational AI, document intelligence, and workflow automation domains. I thrive in cross-functional teams and enjoy turning complex problems into practical, production-ready AI solutions that empower researchers and engineers alike. I’m proficient in Python, PyTorch, TensorFlow, LangChain, FAISS, and FastAPI, with hands-on experience deploying scalable AI services and end-to-end ML solutions. I also excel at refining prompts, designing evaluation pipelines for large language model use cases, and streamlining data ingestion and embedding workflows to boost retrieval accuracy and user experiences in production environments.

Available to hire

I’m Budhilsai Kosireddi, an AI/ML Engineer with a focus on building scalable machine learning models, generative AI applications, and retrieval-augmented generation (RAG) solutions across conversational AI, document intelligence, and workflow automation domains. I thrive in cross-functional teams and enjoy turning complex problems into practical, production-ready AI solutions that empower researchers and engineers alike.

I’m proficient in Python, PyTorch, TensorFlow, LangChain, FAISS, and FastAPI, with hands-on experience deploying scalable AI services and end-to-end ML solutions. I also excel at refining prompts, designing evaluation pipelines for large language model use cases, and streamlining data ingestion and embedding workflows to boost retrieval accuracy and user experiences in production environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

AI/ML Engineer at DeepMind

January 1, 2026 - Present

Built retrieval-augmented AI applications using LangChain, FAISS, and GPT models, enabling research teams to access internal knowledge sources through natural language queries while reducing manual information gathering. Refined prompt workflows and evaluation pipelines for large language model use cases, improving response consistency across research prototypes and shortening iteration cycles. Created FastAPI services to expose ML capabilities across internal apps, supporting secure integration, monitoring requirements, and reliable model consumption in production environments. Collaborated with research scientists and data teams to prepare training datasets, validate model outputs, and troubleshoot performance issues identified during testing and deployment activities. Streamlined document ingestion and embedding processes using Python and Azure services, increasing retrieval accuracy while supporting growing volumes of technical content and research documentation.

Junior AI/ML Engineer at Haptik AI

January 1, 2023 - June 1, 2024

Developed NLP models for chatbots and virtual assistant platforms using Python, Scikit-learn, and BERT-based architectures, improving intent recognition quality across customer support conversations. Processed large conversational data sets through PySpark and Databricks workflows, enhancing data quality and reducing preparation effort required for model training and validation tasks. Integrated ML services with backend applications through REST APIs, enabling real-time predictions and supporting new automation capabilities for enterprise clients. Conducted exploratory data analysis and feature engineering on customer interaction data, identifying behavioral patterns that contributed to measurable gains in model performance. Assisted in deploying ML models through Docker-based environments, supporting release activities, issue resolution, and ongoing monitoring for production AI applications.