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I'm Hannah B., a Senior Machine Learning Engineer with 6+ years of software engineering experience building production-grade ML systems that serve millions of users. I specialize in MLOps, deep learning optimization, and generative AI solutions across fintech and healthcare, and I enjoy turning research into reliable, scalable AI products. I thrive working with cross-functional teams to design end-to-end solutions, reduce latency, and elevate experimentation and governance practices. I’m passionate about delivering impactful AI at scale while ensuring composable, maintainable architectures that comply with industry regulations.…I'm Hannah B., a Senior Machine Learning Engineer with 6+ years of software engineering experience building production-grade ML systems that serve millions of users. I specialize in MLOps, deep learning optimization, and generative AI solutions across fintech and healthcare, and I enjoy turning research into reliable, scalable AI products. I thrive working with cross-functional teams to design end-to-end solutions, reduce latency, and elevate experimentation and governance practices. I’m passionate about delivering impactful AI at scale while ensuring composable, maintainable architectures that comply with industry regulations.

Hannah Billy

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

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I'm Hannah B., a Senior Machine Learning Engineer with 6+ years of software engineering experience building production-grade ML systems that serve millions of users. I specialize in MLOps, deep learning optimization, and generative AI solutions across fintech and healthcare, and I enjoy turning research into reliable, scalable AI products. I thrive working with cross-functional teams to design end-to-end solutions, reduce latency, and elevate experimentation and governance practices. I’m passionate about delivering impactful AI at scale while ensuring composable, maintainable architectures that comply with industry regulations.…I'm Hannah B., a Senior Machine Learning Engineer with 6+ years of software engineering experience building production-grade ML systems that serve millions of users. I specialize in MLOps, deep learning optimization, and generative AI solutions across fintech and healthcare, and I enjoy turning research into reliable, scalable AI products. I thrive working with cross-functional teams to design end-to-end solutions, reduce latency, and elevate experimentation and governance practices. I’m passionate about delivering impactful AI at scale while ensuring composable, maintainable architectures that comply with industry regulations.

Available to hire

I’m Hannah B., a Senior Machine Learning Engineer with 6+ years of software engineering experience building production-grade ML systems that serve millions of users. I specialize in MLOps, deep learning optimization, and generative AI solutions across fintech and healthcare, and I enjoy turning research into reliable, scalable AI products.

I thrive working with cross-functional teams to design end-to-end solutions, reduce latency, and elevate experimentation and governance practices. I’m passionate about delivering impactful AI at scale while ensuring composable, maintainable architectures that comply with industry regulations.

Skills

Experience Level

Expert

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Expert

Work Experience

Lead Machine Learning Engineer at TheCodeGenix

January 1, 2022 - Present

Architected and deployed an NLP-based document processing pipeline using BERT and AWS SageMaker, achieving 94% accuracy on monthly document processing and reducing manual review time and operational costs. Led MLOps initiatives implementing CI/CD pipelines with GitHub Actions, Docker, and Kubernetes, cutting deployment time from 2 weeks to 4 hours and maintaining 99.9% production uptime. Optimized deep learning models for real-time inference with TensorRT and ONNX quantization, reducing latency by 65% for fraud-detection systems handling daily transactions. Built a centralized feature-engineering platform using Apache Spark and Feast, standardizing features across five teams and boosting reproducibility and experiment velocity. Mentored a team of 4 engineers on MLOps, model monitoring, and A/B testing, establishing governance to meet financial regulatory requirements.

Senior Learning Engineer at HealthTech Innovations

January 1, 2020 - January 1, 2022

Developed a computer vision system for medical image analysis using PyTorch and ResNet architectures, achieving strong diagnostic accuracy for early-stage disease detection and deployment across multiple healthcare facilities. Designed a real-time recommendation engine using collaborative filtering and deep learning techniques to deliver daily personalized recommendations and increase user engagement. Implemented MLOps infrastructure on GCP Vertex AI with automated retraining pipelines, reducing model drift incidents by 90% and ensuring continuous model performance in production. Engineered data pipelines processing 10TB+ daily healthcare data with Apache Airflow, BigQuery, and Dataflow, ensuring HIPAA-compliant data handling and sub-second query performance. Conducted A/B tests and statistical analyses on 15+ ML models, translating results into product decisions that improved patient outcome predictions.

Machine Learning Engineer at Goldman Sachs

January 1, 2018 - January 1, 2020

Built a predictive analytics platform using scikit-learn and XGBoost for credit risk assessment, processing loan applications 10x faster with a 15% reduction in default rates. Developed ETL pipelines with Python, SQL, and Apache Spark, consolidating data from 12+ sources into a unified data warehouse and enabling real-time BI dashboards. Engineered fraud detection models using XGBoost and deep learning, processing transactions with precision and preventing losses. Containerized legacy applications using Docker and orchestrated with Kubernetes, improving deployment reliability and reducing infrastructure costs by nearly 40%. Collaborated with product and engineering teams to translate business requirements into technical specifications, delivering 8 major features on time in agile sprints.