At OpenAI, I lead architecture and technical direction for large-scale machine learning systems spanning training, evaluation, inference, and production deployment. I build distributed ML infrastructure and model-serving platforms for high-volume workloads using Python, PyTorch, Kubernetes, and cloud-native technologies.
Previously at Meta, I developed production ML systems for ranking, recommendation, personalization, and prediction, while leading cross-team infrastructure initiatives and mentoring engineers. My work covers distributed training, data processing, feature generation, experimentation, observability, and reliable deployment.
Across KMS Technology, BairesDev, Basho Technologies, Surge AI, and Labelbox, I've built data-intensive software, distributed systems, AI evaluation tasks, and algorithmic benchmarks. I bring 15+ years across backend engineering, cloud infrastructure, data platforms, and production machine learning.
