Arnav Chakravarthy is a Machine Learning Engineer with nine years of experience building production-grade AI systems, currently at Meta after leading ML efforts at a Sequoia-backed GenAI startup. He combines deep research in weakly supervised learning and video captioning from his MS at Arizona State University with hands-on expertise deploying RAG, agentic support pipelines, and Kubernetes-optimized ML workloads. At QueryPal he designed a curriculum-based CodeGen system and a semantic cache that cut latency fivefold and boosted cache hit likelihood 4.5x, and at VMware he applied model-based RL and formal robustness methods to cloud optimization while taking prototypes to production. Comfortable across the stack—PyTorch, TensorFlow, Kubeflow, Go/KubeBuilder and AWS—he bridges academic research on neutralizing information operations with pragmatic infrastructure and evaluation frameworks. Based in San Francisco, he’s adept at turning novel research into resilient, observable systems that scale in enterprise environments.
9 years of coding experience
6 years of employment as a software developer
Bachelor of Technology - BTech Computer Engineering, Bachelor of Technology - BTech Computer Engineering at SVKM's Narsee Monjee Institute of Management Studies (NMIMS)
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Ira A. Fulton Schools of Engineering at Arizona State University
ISC Science, ISC Science at Lilavati Bai Podar Senior Secondary School
A responsive web app to allow remote orders for my college canteen
Contributions:23 pushes, 1 branch in 2 years 7 months
reactcssjavascriptwebappresponsive
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
Arnav Chakravarthy - Machine Learning Engineer at Meta