Karan Grover is a software engineer with 12 years of experience specializing in large-scale distributed systems, cloud-native infrastructure, and ML deployment. He brings production-hardened expertise from Microsoft Research—where he built a secure SGX-backed ML service and a high-throughput blockchain VM orchestration layer—and recent hands-on work at Meta building an A/B testing framework for inference pipelines. Currently at Fetch, he saves significant operational cost and builds multi-region services using Go, Redis, and AWS, and his past work shows a knack for automating complex migrations (e.g., updating 16 billion DynamoDB items at 40k/sec). A UW–Madison master’s student blending systems and ML coursework, he pairs research-driven rigor with practical engineering that speeds onboarding, reduces cost, and scales mission-critical services.
12 years of coding experience
6 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at University of Wisconsin-Madison
Bachelor of Technology (B.Tech.) Computer Science, Bachelor of Technology (B.Tech.) Computer Science at Indraprastha Institute of Information Technology, Delhi
Contributions:25 commits, 18 pushes, 3 tags in 14 days
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