Meta/Production Engineer, Network Infrastructure Security Engineering
New York, NY · Jul 2020 — Present
- Architected and scaled a real-time malicious-traffic (DDoS) detection and mitigation system distributed across a 100K+ host fleet, optimizing for high throughput under strict low-latency constraints. Partnered with security, host-platform, and networking teams to drive the system from MVP to production for L7.
- Optimized low-latency packet-processing pipelines at the host kernel level (
eBPF, XDP, TC) for detection and mitigation protocols, across varied host and NIC hardware (Broadcom, Mellanox).
- Developed quantitative anomaly-detection models using time-series analysis, signal processing, and supervised ML to identify asymmetric network threats from high-volume telemetry.
- Established triage and response processes for DDoS and edge-security incidents. As primary on-call in a 24/7 SOC rotation, assessed dozens of high-profile external security & infra events per shift — drove MTTD down to p50 <1 min via automated anomaly alerting, and MTTR to p50 <3 min (from 10–30 min) via automation and pre-staged mitigation runbooks.
- Mentor junior engineers — onboarding and building the technical skills required for network-security incident response.
Amazon Lab126/SDE Intern, Consumer Devices
Sunnyvale, CA · Sep — Nov 2019
- Designed a high-performance, adaptive, portable service to stream and transcode sensor data from a prototype consumer device, letting developers diagnose low-level hardware sensor issues faster — cut device disk usage by 30% and average time-to-dump-state by 90%.
VMware/Software Engineer Intern, VM Platform
Palo Alto, CA · May — Aug 2019
- Designed and built a scalable, container-runtime-independent solution for managing containers inside a Linux VM, gathering container stats by talking directly to the exposed Linux kernel APIs that make containerization feasible.
Georgia Tech/Research & Teaching
Atlanta, GA · Aug 2016 — May 2020
Undergraduate Researcher — Dr. Taesoo Kim · Fuzzification: Anti-Fuzzing Techniques
- Designed and evaluated anti-fuzzing techniques to slow modern fuzzers and protect software from malicious fuzzing. Paper accepted by USENIX Security.
Undergraduate Researcher — Dr. Joy Arulraj · Accelerating Data Analytics with Logical Zone Maps
- Aided design of new logical indexing structures for caching statistical aggregates over subsets of data.
Undergraduate Teaching Assistant — Design & Analysis of Operating Systems
- Taught operating-systems concepts and kernel programming; graded and maintained assignments.