Machine Learning Engineer
Building and deploying ML infrastructure at scale. This is where theory meets production — designing systems that actually work in the real world, not just in Jupyter notebooks.
What I Do
- ML Infrastructure: Design, build, and maintain scalable and reliable machine learning infrastructure.
- Model Deployment: Deploy and monitor ML models for real-time inference.
- API Development: Develop and maintain robust REST APIs for the company's machine learning services.
- Production Collaboration: Collaborate with data scientists to productionalize their models and algorithms.