Nisha Johnson
AI Infrastructure Product Leader | TPUs, GPUs, Kubernetes | Scaling $B+ AI Compute Platforms at Google Cloud
- Role
- Product Management Lead (Ray on Gke for Tpus and Gpus) at Google
- Location
- Mountain View, CA, US
- LinkedIn followers
- 500 followers
About Nisha Johnson
Product leader working at the intersection of AI infrastructure, large-scale compute, and developer platforms.At Google Cloud I lead products spanning TPUs, GPUs, ML frameworks, and Kubernetes infrastructure used for training and serving frontier AI models. My work has included defining product strategy for multi-billion-dollar compute platforms, launching large-scale training technologies, and building partnerships with ecosystem leaders including Hugging Face, Anyscale, and vLLM.I enjoy turning ambiguous technical opportunities into concrete products - from early customer discovery through roadmap definition, cross-org alignment, and large-scale launch.Previously at Synopsys I worked on semiconductor design tools and distributed compute infrastructure for chip design.I hold an MBA (Finance) from Imperial College London and an MS (ECE) from Carnegie Mellon University.
Experience
Product Management Lead (Ray on Gke for Tpus and Gpus)
Apr 2025 — Present · Mountain View, CA, US
Leading product strategy across the full AI compute stack (TPU hardware, ML frameworks, and Kubernetes orchestration) supporting frontier AI model development- Led product strategy and execution to grow revenue by 2x to hit high annually- Identified gaps in product and influenced partners to prioritize fixes to retain GKE AI\'s top-10 customer revenue (full stack improvements across observability, security, TPU enablement)- Created product definitions for foundational Ray on kubernetes features unlocking new value for customers in usability, performance and compute obtainability:https://cloud.google.com/blog/products/containers-kubernetes/ray-on-tpus-with-gke-a-more-native-experiencehttps://cloud.google.com/blog/products/containers-kubernetes/ray-on-gke-new-features-for-ai-scheduling-and-scaling
Education
Carnegie Mellon University
Master of Science - MS, Electrical and Computer Engineering
College of Engineering Trivandrum
Bachelor of Technology - BTech, Electronics and Communications Engineering
Imperial College London
Master of Business Administration - MBA, Finance
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