Open to opportunities

Paul Bailey

@paulbailey

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Senior AI Developer with expertise in machine learning solutions.

United States

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What I'm looking for

I am looking for a role that challenges me with innovative AI projects and fosters a collaborative culture.

I am a Senior AI Developer with over 11 years of experience in delivering advanced AI and machine learning solutions. My expertise lies in designing, training, and deploying large-scale models for natural language processing, computer vision, and predictive analytics. I have a proven track record of achieving state-of-the-art accuracy in enterprise applications, leveraging frameworks such as TensorFlow and PyTorch.

Throughout my career, I have successfully built scalable MLOps pipelines and real-time recommendation engines that significantly improve business outcomes. My work has led to increased conversion rates and enhanced customer retention strategies. I am passionate about integrating AI technologies with enterprise systems, ensuring seamless interoperability and low-latency performance for real-time applications.

In addition to my technical skills, I prioritize AI ethics and compliance, ensuring fairness and transparency in all deployed models. I thrive in collaborative environments and have led Agile teams to deliver impactful AI-driven insights that foster data-driven decision-making across organizations.

Experience

Work history, roles, and key accomplishments

Current

Senior AI Engineer

Current

Dumbstruck

May 2021 - Present (4 years 2 months)

Designed and deployed deep learning models using PyTorch and TensorFlow for NLP and vision tasks, achieving state-of-the-art accuracy for large-scale enterprise applications. Built scalable MLOps pipelines with MLflow and Kubernetes, reducing model deployment time by 50% and ensuring reproducibility across environments.

PyTorch TensorFlow NLP Computer Vision MLOps MLFlow Kubernetes fastAPI Docker

Lead Machine Learning Engineer

Talage

May 2017 - Mar 2021 (3 years 10 months)

Architected predictive modeling solutions using scikit-learn and XGBoost for churn prediction, improving customer retention strategies by 18% across SaaS platforms. Built custom NLP pipelines leveraging BERT and Hugging Face Transformers for text classification and sentiment analysis with 96% accuracy.

scikit learn XGBoost NLP BERT Apache Spark AWS Lambda Agile

AI / Data Scientist

Adaptiva

Jun 2014 - Mar 2017 (2 years 9 months)

Designed time-series forecasting models using ARIMA and LSTM networks for demand prediction, improving forecasting accuracy by 20%. Built image recognition pipelines using CNN architectures in TensorFlow for automated defect detection in manufacturing processes.