About
Who I Am
I am a Software Development Engineer at Amazon Web Services, working on the SageMaker Unified Studio Data Engineering team. I build scalable machine learning infrastructure and develop next-generation workflow management features. I spearheaded UI development for the SageMaker Model Hub: Foundation Models using React and TypeScript, improving model discovery and deployment efficiency by 40%. My work spans full-stack development, data pipeline engineering with AWS Lambda and Glue, and maintaining high-availability distributed systems with 99.9% reliability.
Previously, I focused on machine learning research and AI applications across healthcare and lab automation. At UC Davis Health, I built RAG systems for clinical trial analysis using fine-tuned LLMs (GPT-4, Llama3), and developed video prediction models to detect aneurysms in CT scans. At Tetsuwan Scientific, I engineered an AI-integrated platform for wet lab robotics, implementing multi-agent systems and voice transcription to accelerate bio-chemistry research workflows by 250%. I've also contributed to statistical analysis at Lawrence Livermore National Laboratory and built full-stack anomaly detection platforms at T-Mobile.
Skills
Technologies I Use
AWS
Python
TensorFlow
PyTorch
PostgreSQL
LangChain
Next.js
React.js
TypeScript
Node.js
Docker
Google Cloud
Experience
Where I've Worked
Software Development Engineer
@Amazon Web Services (AWS)
July 2025 - Present
- •Contributed to the SageMaker Unified Studio Data Engineering team, developing next-generation machine learning workflow and model management features integrated with AWS's latest service offerings.
- •Spearheaded UI development for the new SageMaker Model Hub: Foundation Models, building scalable React/TypeScript components and integrating AWS APIs and CloudFormation resources, improving model discovery and deployment efficiency by 40%.
- •Collaborated cross-functionally with Product Managers, UX Designers, and Senior/Principal Engineers to deliver high-impact releases under strict deadlines, consistently meeting AWS's Raising the Bar engineering standards.
- •Developed and maintained data ingestion and monitoring pipelines for SageMaker Unified Studio and EMR Studio using AWS Lambda, S3, CloudWatch, and Glue, ensuring high availability and operational excellence.
- •Handled on-call responsibilities, triaging and resolving production incidents across distributed services to maintain ≥99.9% reliability SLAs and deliver rapid customer issue resolution.
- •Authored internal documentation, design proposals, and operational playbooks to improve team onboarding, knowledge sharing, and long-term system scalability.
Software Development Engineer
@Amazon Web Services (AWS)
July 2025 - Present
- •Contributed to the SageMaker Unified Studio Data Engineering team, developing next-generation machine learning workflow and model management features integrated with AWS's latest service offerings.
- •Spearheaded UI development for the new SageMaker Model Hub: Foundation Models, building scalable React/TypeScript components and integrating AWS APIs and CloudFormation resources, improving model discovery and deployment efficiency by 40%.
- •Collaborated cross-functionally with Product Managers, UX Designers, and Senior/Principal Engineers to deliver high-impact releases under strict deadlines, consistently meeting AWS's Raising the Bar engineering standards.
- •Developed and maintained data ingestion and monitoring pipelines for SageMaker Unified Studio and EMR Studio using AWS Lambda, S3, CloudWatch, and Glue, ensuring high availability and operational excellence.
- •Handled on-call responsibilities, triaging and resolving production incidents across distributed services to maintain ≥99.9% reliability SLAs and deliver rapid customer issue resolution.
- •Authored internal documentation, design proposals, and operational playbooks to improve team onboarding, knowledge sharing, and long-term system scalability.
Software Development Engineer
@Amazon Web Services (AWS)
July 2025 - Present
- •Contributed to the SageMaker Unified Studio Data Engineering team, developing next-generation machine learning workflow and model management features integrated with AWS's latest service offerings.
- •Spearheaded UI development for the new SageMaker Model Hub: Foundation Models, building scalable React/TypeScript components and integrating AWS APIs and CloudFormation resources, improving model discovery and deployment efficiency by 40%.
- •Collaborated cross-functionally with Product Managers, UX Designers, and Senior/Principal Engineers to deliver high-impact releases under strict deadlines, consistently meeting AWS's Raising the Bar engineering standards.
- •Developed and maintained data ingestion and monitoring pipelines for SageMaker Unified Studio and EMR Studio using AWS Lambda, S3, CloudWatch, and Glue, ensuring high availability and operational excellence.
- •Handled on-call responsibilities, triaging and resolving production incidents across distributed services to maintain ≥99.9% reliability SLAs and deliver rapid customer issue resolution.
- •Authored internal documentation, design proposals, and operational playbooks to improve team onboarding, knowledge sharing, and long-term system scalability.
Software Development Engineer
@Amazon Web Services (AWS)
July 2025 - Present
- •Contributed to the SageMaker Unified Studio Data Engineering team, developing next-generation machine learning workflow and model management features integrated with AWS's latest service offerings.
- •Spearheaded UI development for the new SageMaker Model Hub: Foundation Models, building scalable React/TypeScript components and integrating AWS APIs and CloudFormation resources, improving model discovery and deployment efficiency by 40%.
- •Collaborated cross-functionally with Product Managers, UX Designers, and Senior/Principal Engineers to deliver high-impact releases under strict deadlines, consistently meeting AWS's Raising the Bar engineering standards.
- •Developed and maintained data ingestion and monitoring pipelines for SageMaker Unified Studio and EMR Studio using AWS Lambda, S3, CloudWatch, and Glue, ensuring high availability and operational excellence.
- •Handled on-call responsibilities, triaging and resolving production incidents across distributed services to maintain ≥99.9% reliability SLAs and deliver rapid customer issue resolution.
- •Authored internal documentation, design proposals, and operational playbooks to improve team onboarding, knowledge sharing, and long-term system scalability.
