Maneesh Varshney
Principal Staff Software Engineer at LinkedIn
San Jose, California, United States
Summary
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Senior🎓
Top SchoolManeesh Varshney is a Principal Staff Software Engineer with 13 years of experience building the infrastructure that enables large-scale AI, from GPU superclusters to distributed training platforms and hardware–software co-design. At LinkedIn he led Project Meru’s ML track to deliver a $200M+, 5,000+ GPU supercluster and raised effective GPU utilization from ~5% to ~70%, while also driving the migration from Hadoop-era workloads into Kubernetes with multi-region training. He scaled recommendation models 10,000x, cut training and refresh times by orders of magnitude, and launched the first large personalization models that moved business metrics. He also designed a production FPGA inference accelerator with a PyTorch-to-Verilog compiler that matched H100 latency at 4–5× lower power, demonstrating practical hardware innovation beyond software optimizations. A PhD from UCLA with 11 patents, Maneesh excels in ambiguous, long-horizon problems where close coupling of modeling, systems, and hardware yields disproportionate gains. He’s seeking Principal Staff / Distinguished Engineer roles focusing on hardware efficiency, model scale, and system reliability.
13 years of coding experience
16 years of employment as a software developer
Indian Institute of Technology KanpurUniversity of California, Los Angeles
Github Skills (1)
hadoop6
Programming languages (1)
Github contributions (5)
mvarshney/writing
Jul 2019 - Apr 2023
Contributions:50 pushes, 1 branch in 3 years 9 months
LinkedInAttic/Cubert
Sep 2014 - Nov 2014
Fast and efficient batch computation engine for complex analysis and reporting of massive datasets on Hadoop
Contributions:16 commits in 1 month
hadoop
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