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I'm an AI/ML Engineer with 3+ years of hands-on experience building machine learning models and large language model applications. I’m certified in Generative AI with expertise in RAG, NLP, and model fine-tuning. I enjoy turning data into practical solutions that drive business impact. I'm passionate about NLP, retrieval-augmented generation, and deploying scalable ML pipelines from data preprocessing to production. I strive to deliver AI solutions with measurable results and collaborate effectively with cross-functional teams.…I'm an AI/ML Engineer with 3+ years of hands-on experience building machine learning models and large language model applications. I’m certified in Generative AI with expertise in RAG, NLP, and model fine-tuning. I enjoy turning data into practical solutions that drive business impact. I'm passionate about NLP, retrieval-augmented generation, and deploying scalable ML pipelines from data preprocessing to production. I strive to deliver AI solutions with measurable results and collaborate effectively with cross-functional teams.

Laxminarayana Yaga

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

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I'm an AI/ML Engineer with 3+ years of hands-on experience building machine learning models and large language model applications. I’m certified in Generative AI with expertise in RAG, NLP, and model fine-tuning. I enjoy turning data into practical solutions that drive business impact. I'm passionate about NLP, retrieval-augmented generation, and deploying scalable ML pipelines from data preprocessing to production. I strive to deliver AI solutions with measurable results and collaborate effectively with cross-functional teams.…I'm an AI/ML Engineer with 3+ years of hands-on experience building machine learning models and large language model applications. I’m certified in Generative AI with expertise in RAG, NLP, and model fine-tuning. I enjoy turning data into practical solutions that drive business impact. I'm passionate about NLP, retrieval-augmented generation, and deploying scalable ML pipelines from data preprocessing to production. I strive to deliver AI solutions with measurable results and collaborate effectively with cross-functional teams.

Available to hire

I’m an AI/ML Engineer with 3+ years of hands-on experience building machine learning models and large language model applications. I’m certified in Generative AI with expertise in RAG, NLP, and model fine-tuning. I enjoy turning data into practical solutions that drive business impact.

I’m passionate about NLP, retrieval-augmented generation, and deploying scalable ML pipelines from data preprocessing to production. I strive to deliver AI solutions with measurable results and collaborate effectively with cross-functional teams.

Skills

Experience Level

Expert

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Intermediate

Work Experience

AI/ML Engineer at PNC Financial Services Missouri, USA

September 1, 2024 - October 27, 2025

Led development of supervised and unsupervised ML models in PySpark, TensorFlow, and XGBoost to detect fraudulent transactions, reducing false positives by 18% and improving detection. Optimized credit risk scoring with PCA and ensemble methods, boosting predictive performance by 12%. Built NLP pipelines using BERT, GPT-4, and NER to automate document classification and regulatory checks, cutting manual review time by 30%. Designed a Retrieval-Augmented Generation (RAG) system with LangChain, LLaMA, and LlamaIndex to process over 5 million records, increasing analyst research efficiency by 40%. Automated model evaluation and MLOps on Azure with CI/CD, reducing deployment cycles from weeks to days. Created real-time Power BI dashboards with PostgreSQL backend to monitor loan portfolio health and flag high-risk loans earlier.

ML Engineer at Zensar Technologies India

July 1, 2023 - July 1, 2023

Prototyped and evaluated multiple deep learning architectures using Keras and PyTorch, accelerating development cycles by 20%. Engineered feature engineering and time-series forecasting to improve demand accuracy by 14%. Built ML pipelines with Decision Trees, Random Forests, Naive Bayes, K-Means, DBSCAN, delivering client-specific predictive and clustering solutions that improved decision-making by up to 35%. Implemented CNNs and NLP workflows with BERT, NLTK, and Spacy, enhancing text classification and sentiment analysis on large-scale feedback datasets by 20-25%. Managed unstructured data in MongoDB and deployed production-ready models on AWS SageMaker, Lambda, and CloudFormation, achieving 99.9% availability. Created dashboards in Plotly and Tableau for real-time KPI monitoring, reducing reporting lag by 40%. Integrated FastAPI and Streamlit interfaces to operationalize ML apps, cutting manual intervention by 30%. Optimized data handling with Pandas, NumPy, SciPy, reducing pipelin