NXP MLOps Engineering
@ NXP
Built ML pipelines and infrastructure for Machine Learning models worth millions. Deployed AI Chatbot to production, revolutionizing designer access to information.
Technologies
Key Highlights
- Built pipelines for ML models worth millions using CDK and SageMaker
- Deployed AI Chatbot to production using Ansible, CDK, and Bedrock
- Led development of project management app for secure IP access
- Trained multiple teams on CI/CD best practices
The Challenge
When joining NXP’s Hardware Design Analytics team, data scientists were great at creating statistical and ML models, but deployment automation was something they could only dream about. The team needed:
- Simple, reproducible development environments
- Dependable CI/CD pipelines
- Production-ready deployments
The Solution
I brought DevOps excellence to the ML workflow:
ML Pipeline Infrastructure
Built complete infrastructure for training and deploying ML models using AWS CDK and SageMaker. These models provide predictive analytics for hardware design, delivering value worth millions.
AI Chatbot Deployment
Brought an AI-powered chatbot to production using a combination of Ansible, AWS CDK, and Amazon Bedrock. This revolutionized how designers access technical information.
Project Management Application
Led development of a Django-based application running on ECS, enabling secure access to intellectual property across teams.
CI/CD Training & Support
Helped multiple teams level up their ways of working through hands-on training and support in GitLab CI/CD processes.
Technologies Used
- Cloud: AWS (CDK, SageMaker, Bedrock, ECS)
- Backend: Python, Django
- Infrastructure: Ansible
- CI/CD: GitLab CI