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AI/ML Engineer with 4+ years of experience building and deploying scalable solutions across NLP, predictive analytics, and generative AI. Strong foundation in Python and SQL, with hands-on model development and performance optimization using Scikit-learn, TensorFlow, and PyTorch. Experienced in LLM-powered applications using LangChain, Hugging Face, and RAG architectures with vector databases for intelligent automation. Skilled in data engineering with Pandas, NumPy, PySpark, Kafka, and Airflow, and in production-grade MLOps with MLflow, Docker, Kubernetes, and CI/CD on AWS/Azure/GCP.…AI/ML Engineer with 4+ years of experience building and deploying scalable solutions across NLP, predictive analytics, and generative AI. Strong foundation in Python and SQL, with hands-on model development and performance optimization using Scikit-learn, TensorFlow, and PyTorch. Experienced in LLM-powered applications using LangChain, Hugging Face, and RAG architectures with vector databases for intelligent automation. Skilled in data engineering with Pandas, NumPy, PySpark, Kafka, and Airflow, and in production-grade MLOps with MLflow, Docker, Kubernetes, and CI/CD on AWS/Azure/GCP.

Sai Kiran Reddy Rajamuri

AI Engineer, Data Scientist, Software Engineer, +3

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AI/ML Engineer with 4+ years of experience building and deploying scalable solutions across NLP, predictive analytics, and generative AI. Strong foundation in Python and SQL, with hands-on model development and performance optimization using Scikit-learn, TensorFlow, and PyTorch. Experienced in LLM-powered applications using LangChain, Hugging Face, and RAG architectures with vector databases for intelligent automation. Skilled in data engineering with Pandas, NumPy, PySpark, Kafka, and Airflow, and in production-grade MLOps with MLflow, Docker, Kubernetes, and CI/CD on AWS/Azure/GCP.…AI/ML Engineer with 4+ years of experience building and deploying scalable solutions across NLP, predictive analytics, and generative AI. Strong foundation in Python and SQL, with hands-on model development and performance optimization using Scikit-learn, TensorFlow, and PyTorch. Experienced in LLM-powered applications using LangChain, Hugging Face, and RAG architectures with vector databases for intelligent automation. Skilled in data engineering with Pandas, NumPy, PySpark, Kafka, and Airflow, and in production-grade MLOps with MLflow, Docker, Kubernetes, and CI/CD on AWS/Azure/GCP.

Available to hire

AI/ML Engineer with 4+ years of experience building and deploying scalable solutions across NLP, predictive analytics, and generative AI. Strong foundation in Python and SQL, with hands-on model development and performance optimization using Scikit-learn, TensorFlow, and PyTorch.

Experienced in LLM-powered applications using LangChain, Hugging Face, and RAG architectures with vector databases for intelligent automation. Skilled in data engineering with Pandas, NumPy, PySpark, Kafka, and Airflow, and in production-grade MLOps with MLflow, Docker, Kubernetes, and CI/CD on AWS/Azure/GCP.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Work Experience

AI/ML Engineer at HCL Tech

January 1, 2025 - Present

Designed and deployed LLM-driven solutions using LangChain, OpenAI APIs, and RAG architectures to improve document intelligence accuracy by 35% and reduce manual effort across financial use cases. Built Python microservices for real-time model inference with sub-100ms latency for high-throughput financial transaction and risk analysis. Developed and optimized ML models for risk scoring and anomaly detection, improving prediction precision by 25%. Implemented semantic search using FAISS and Pinecone to boost retrieval relevance by 40%. Built end-to-end MLOps pipelines with MLflow, Docker, and Kubernetes, reducing release cycles by 50% and supporting monitoring/version control. Engineered scalable data pipelines with PySpark, Pandas, and NumPy, improving performance by 30%. Leveraged AWS services for training, deployment, and storage, improving scalability and reducing infrastructure costs by 20%. Collaborated with stakeholders to deliver production-ready AI solutions, improving delivery

AI/ML Engineer at Mindtree

July 1, 2020 - July 1, 2023

Developed and deployed machine learning models for classification, regression, and clustering using Scikit-learn and TensorFlow, improving prediction accuracy by ~20%. Built and optimized data preprocessing pipelines with Pandas, NumPy, and PySpark, reducing preparation time by 35% and improving data quality/consistency. Designed computer vision solutions using OpenCV and YOLO for image classification and object detection, improving production detection accuracy by 25%. Developed NLP solutions and early-stage LLM-based applications with Hugging Face and prompt engineering, improving text processing efficiency by 30%. Built RESTful APIs using FastAPI in a microservices architecture, reducing response times by 20%. Created dashboards and reporting with Tableau and Power BI for KPI monitoring. Implemented model monitoring and CI/CD workflows to reduce model-related issues by 30% and improve deployment reliability.