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I am an accomplished AI/ML Engineer with over 1.8 years of progressive experience across Data Engineering, Data Science, and AI/ML solution development. I have demonstrated expertise in designing, building, and deploying scalable data pipelines, predictive models, and advanced generative AI applications. I am skilled in leveraging Big Data ecosystems, cloud platforms like AWS and GCP, and best MLOps practices to deliver measurable business impact and streamline complex workflows. I am committed to driving innovation through AI-powered solutions, focusing strongly on intelligent automation and solving high-impact, real-world challenges. I continuously collaborate with cross-functional teams and institutionalize Responsible AI frameworks to ensure fairness, interpretability, and compliance in business workflows.…I am an accomplished AI/ML Engineer with over 1.8 years of progressive experience across Data Engineering, Data Science, and AI/ML solution development. I have demonstrated expertise in designing, building, and deploying scalable data pipelines, predictive models, and advanced generative AI applications. I am skilled in leveraging Big Data ecosystems, cloud platforms like AWS and GCP, and best MLOps practices to deliver measurable business impact and streamline complex workflows. I am committed to driving innovation through AI-powered solutions, focusing strongly on intelligent automation and solving high-impact, real-world challenges. I continuously collaborate with cross-functional teams and institutionalize Responsible AI frameworks to ensure fairness, interpretability, and compliance in business workflows.

Raviteja Tiruveedhu

AI Engineer, Data Scientist, AI Developer, +1

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I am an accomplished AI/ML Engineer with over 1.8 years of progressive experience across Data Engineering, Data Science, and AI/ML solution development. I have demonstrated expertise in designing, building, and deploying scalable data pipelines, predictive models, and advanced generative AI applications. I am skilled in leveraging Big Data ecosystems, cloud platforms like AWS and GCP, and best MLOps practices to deliver measurable business impact and streamline complex workflows. I am committed to driving innovation through AI-powered solutions, focusing strongly on intelligent automation and solving high-impact, real-world challenges. I continuously collaborate with cross-functional teams and institutionalize Responsible AI frameworks to ensure fairness, interpretability, and compliance in business workflows.…I am an accomplished AI/ML Engineer with over 1.8 years of progressive experience across Data Engineering, Data Science, and AI/ML solution development. I have demonstrated expertise in designing, building, and deploying scalable data pipelines, predictive models, and advanced generative AI applications. I am skilled in leveraging Big Data ecosystems, cloud platforms like AWS and GCP, and best MLOps practices to deliver measurable business impact and streamline complex workflows. I am committed to driving innovation through AI-powered solutions, focusing strongly on intelligent automation and solving high-impact, real-world challenges. I continuously collaborate with cross-functional teams and institutionalize Responsible AI frameworks to ensure fairness, interpretability, and compliance in business workflows.

Available to hire

I am an accomplished AI/ML Engineer with over 1.8 years of progressive experience across Data Engineering, Data Science, and AI/ML solution development. I have demonstrated expertise in designing, building, and deploying scalable data pipelines, predictive models, and advanced generative AI applications. I am skilled in leveraging Big Data ecosystems, cloud platforms like AWS and GCP, and best MLOps practices to deliver measurable business impact and streamline complex workflows.

I am committed to driving innovation through AI-powered solutions, focusing strongly on intelligent automation and solving high-impact, real-world challenges. I continuously collaborate with cross-functional teams and institutionalize Responsible AI frameworks to ensure fairness, interpretability, and compliance in business workflows.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Work Experience

AI/ML Engineer at Tungsten Automation, USA

July 1, 2025 - August 23, 2025

Architected and deployed generative AI–driven copilots, automating development and data extraction workflows to accelerate model deployment cycles by up to 80%. Designed and fine-tuned advanced NLP solutions using large language models with Hugging Face Transformers for document comprehension and automated insight generation. Developed scalable MLOps pipelines with Kubeflow and Docker enabling continuous AI model integration and deployment. Collaborated with product and engineering teams to embed AI functionalities in flagship solutions, improving invoice processing accuracy and straight-through processing rates. Engineered enterprise-grade AI/ML infrastructure on AWS and Google Cloud ensuring high availability and fault tolerance. Executed complex computer vision projects for intelligent document analysis. Implemented Responsible AI frameworks with Explainable AI to ensure fairness and compliance. Led research in next-generation AI algorithms for workflow optimization and automation

Machine Learning Engineer at DIG IT DIGITAL 360, India

January 31, 2023 - August 23, 2025

Developed and automated end-to-end machine learning workflows using Azure Machine Learning Pipelines to streamline data preprocessing, model training, and deployment. Authored reusable Python scripts and Jupyter Notebooks for data exploration, feature engineering, and outlier detection. Enhanced model performance via hyperparameter optimization using GridSearchCV and RandomizedSearchCV. Deployed production-ready ML models as RESTful endpoints integrated via FastAPI and Swagger. Created interactive Power BI dashboards for visualizing model metrics and feature importance to support decision making. Engineered version-controlled data pipelines with Azure Data Factory for scheduled ingestion, transformation, and automated model retraining. Implemented CI/CD best practices with Git and Azure DevOps ensuring reliable and scalable ML production deployments.