I focus on translating ambiguous requirements into concrete architectures, providing large-scale, data-intensive system solutions for ML workloads.
My recent work spans inference serving, resource scheduling, distributed systems, and cloud infrastructure. Currently researching production-scale job scheduling with CMU Parallel Data Lab in collaboration with Uber.
Past life: Backend Engineer & Data Scientist
Graduating Dec 2026 | Open to AI/Cloud Infra, Solutions Architect, and MLE/SWE roles.
Feel free to reach out!


