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I am an AI/ML Engineer with around 4 years of experience designing, developing, and deploying scalable machine learning and AI solutions. I transform raw data into actionable insights, optimize ML workflows, and deliver high-performance AI models to drive business innovation. I am proficient in cloud platforms such as AWS, Azure, and GCP, and I build data visualization dashboards using Tableau, Power BI, and SQL Server. I have hands-on experience with Generative AI, BERT, GPT-4, and large language models (LLMs) for advanced NLP applications, including Named Entity Recognition (NER). I am proficient in Python, scikit-learn, TensorFlow, XGBoost, and implementing MLOps and CI/CD pipelines to streamline model deployment.…I am an AI/ML Engineer with around 4 years of experience designing, developing, and deploying scalable machine learning and AI solutions. I transform raw data into actionable insights, optimize ML workflows, and deliver high-performance AI models to drive business innovation. I am proficient in cloud platforms such as AWS, Azure, and GCP, and I build data visualization dashboards using Tableau, Power BI, and SQL Server. I have hands-on experience with Generative AI, BERT, GPT-4, and large language models (LLMs) for advanced NLP applications, including Named Entity Recognition (NER). I am proficient in Python, scikit-learn, TensorFlow, XGBoost, and implementing MLOps and CI/CD pipelines to streamline model deployment.

Jaswanth Reddy Gopu

Data Scientist, AI Engineer, Full Stack Developer, +4

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I am an AI/ML Engineer with around 4 years of experience designing, developing, and deploying scalable machine learning and AI solutions. I transform raw data into actionable insights, optimize ML workflows, and deliver high-performance AI models to drive business innovation. I am proficient in cloud platforms such as AWS, Azure, and GCP, and I build data visualization dashboards using Tableau, Power BI, and SQL Server. I have hands-on experience with Generative AI, BERT, GPT-4, and large language models (LLMs) for advanced NLP applications, including Named Entity Recognition (NER). I am proficient in Python, scikit-learn, TensorFlow, XGBoost, and implementing MLOps and CI/CD pipelines to streamline model deployment.…I am an AI/ML Engineer with around 4 years of experience designing, developing, and deploying scalable machine learning and AI solutions. I transform raw data into actionable insights, optimize ML workflows, and deliver high-performance AI models to drive business innovation. I am proficient in cloud platforms such as AWS, Azure, and GCP, and I build data visualization dashboards using Tableau, Power BI, and SQL Server. I have hands-on experience with Generative AI, BERT, GPT-4, and large language models (LLMs) for advanced NLP applications, including Named Entity Recognition (NER). I am proficient in Python, scikit-learn, TensorFlow, XGBoost, and implementing MLOps and CI/CD pipelines to streamline model deployment.

Available to hire

I am an AI/ML Engineer with around 4 years of experience designing, developing, and deploying scalable machine learning and AI solutions. I transform raw data into actionable insights, optimize ML workflows, and deliver high-performance AI models to drive business innovation.

I am proficient in cloud platforms such as AWS, Azure, and GCP, and I build data visualization dashboards using Tableau, Power BI, and SQL Server. I have hands-on experience with Generative AI, BERT, GPT-4, and large language models (LLMs) for advanced NLP applications, including Named Entity Recognition (NER). I am proficient in Python, scikit-learn, TensorFlow, XGBoost, and implementing MLOps and CI/CD pipelines to streamline model deployment.

Skills

Experience Level

Expert

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Intermediate

Work Experience

AI/ML Engineer at State Farm, USA

January 1, 2025 - November 18, 2025

Led end-to-end ML/AI initiatives including feature engineering, model selection, and cross-validated pipelines to deliver robust forecasting for operations. Built domain-specific NLU using LLaMA with multilingual data, achieving a 92% improvement in semantic accuracy and reduced hallucinations through adaptive tokenization and prompt-tuning. Implemented CI/CD pipelines for ML models using MLflow, Docker, and Kubernetes, enabling scalable deployments across AWS SageMaker and GCP Vertex AI. Developed NER systems with spaCy and custom-trained transformers to automate domain-entity extraction. Created GAN-based data augmentation workflows integrated with LangChain to enhance synthetic data quality for training conversational AI. Deployed hybrid LLM architectures combining BERT embeddings with GPT-4 for improved natural language inference and chatbot coherence. Designed scalable PostgreSQL schemas to support model-ready datasets.

AI/ML Engineer at HCL Tech, India

July 1, 2022 - July 1, 2022

Implemented Decision Tree and Random Forest models for customer churn prediction, achieving a 25% improvement in accuracy through hyperparameter tuning with GridSearchCV. Conducted hypothesis testing and CNN-based image recognition, boosting classification precision by 27% via architecture fine-tuning and dropout regularization. Built AWS-based ML infrastructure (EMR, EC2) integrated with Scikit-learn and XGBoost, delivering predictive analytics visualized in Tableau and accelerating time-to-insight. Optimized Retrieval-Augmented Generation (RAG) pipelines with contextual vector databases for enhanced document retrieval in enterprise chatbots. Deployed models on AWS SageMaker and Azure ML Studio with Docker/Kubernetes for scalable inference. Performed EDA with NumPy/Pandas/Matplotlib and applied transfer learning with TensorFlow for image/text tasks to improve accuracy and reduce training time.

AI/ML Engineer at State Farm

January 1, 2025 - November 18, 2025

Established multiple ML pipelines leveraging regression models with extensive feature engineering, hyperparameter tuning, and cross-validation to deliver robust operational forecasts. Built domain-specific LLaMA models achieving a 92% improvement in semantic accuracy and reduced hallucinations via adaptive tokenization and prompt tuning across multilingual datasets. Implemented end-to-end CI/CD pipelines for ML models using MLflow, Docker, and Kubernetes, enabling scalable deployments on AWS SageMaker and GCP Vertex AI. Developed NER systems using spaCy and custom-trained transformers to automatically extract and label domain entities. Engineered GAN-based data augmentation with LangChain to enhance synthetic data for training and context-aware conversational AI. Deployed hybrid LLM architectures combining BERT for contextual embeddings and GPT-4 for generative reasoning, increasing natural language inference accuracy by 95% and improving chatbot fluency. Designed relational databases

AI/ML Engineer at HCL Tech

July 1, 2022 - July 1, 2022

Applied Decision Tree and Random Forest models achieving 25% model accuracy improvements for customer churn prediction, optimizing hyperparameters with GridSearchCV. Executed hypothesis testing and CNN-based image recognition, improving classification precision by 27% through architecture tuning and dropout. Created AWS-based ML infrastructure (EMR, EC2) integrated with Scikit-learn and XGBoost for scalable data processing, visualized via Tableau dashboards, delivering faster model-to-insight delivery by 70%. Optimized Retrieval-Augmented Generation (RAG) pipelines with LLMs and contextual vector databases for improved document retrieval relevance in enterprise chatbot solutions. Deployed ML models on AWS SageMaker and Azure ML Studio, using Docker and Kubernetes for scalable inference. Performed EDA with NumPy, Pandas, and Matplotlib, enabling data-driven insights and improving forecasting accuracy by 30%. Employed TensorFlow for image and text classification with transfer learning to