Founding engineer at a startup responsible for the backend performance, infrastructure, and deployment of an ML project.
• Reduced data processing time by 80% (4 hours to 45 minutes) by redesigning the backend to distribute
workloads across Kubernetes-orchestrated containers.
• Decreased time taken for bug root cause identification from 4 hours to real time by implementing centralized
logging for a distributed system using EFK (Elasticsearch, Fluentd, Kibana) to address the observability gap.
• Reduced Azure cloud costs by 30% by re-architecting VM utilization and optimizing Node.js process scaling.
• Enhanced code quality and standards by writing 50+ code reviews and mentoring junior developers.