Leadership foundation · India · National Institute of Engineering
Early exposure to computers in high school sparked curiosity and problem solving. From becoming a class captain to leading cultural and finance committees, I gained early experience in leadership, communication, and empathy. Computer Science then gave those habits a technical foundation.
Embedded systems · India
Embedded software, device drivers, and graphics/software layers built a foundation for understanding what sits beneath the product experience—and made humility and team care central lessons from the first team.
Devices + sensors · India
Camera sensor and camera software work, together with mobile chip bring-up, strengthened an understanding of how imaging, device software, and hardware/software integration create mobile experiences.
Data → ML · US · Seattle
Search-engine ingestion and knowledge graphs led to ML inference and DNN techniques for structured and unstructured data extraction. A chatbot hackathon opened product management and the opportunity to build an AI product from 0-to-1.
Distributed platforms · US · Seattle
B2B supply-chain systems and microservices revealed how distributed platforms power customer outcomes. It was also a formative engineering-management chapter: delivering through COVID with empathy and clarity.
Consumer platform · UK · London
Creator Marketplace combined ML platform work with a B2C ads-domain and consumer-platform context—supporting creators and businesses while incorporating user feedback, policy, and cross-geo perspectives.
Database infrastructure · US · Seattle
Building a distributed SQL database control plane provided broad exposure to the connected layers of a database platform and to the discipline of bringing greenfield infrastructure to life.
AI infrastructure · US · Seattle
Inference platform work brought distributed systems and AI together through asynchronous inference, scheduling optimization, and platform capacity for high-throughput AI workloads.
Model + hardware boundary · US · Bay Area
TPU simulation and LLM model-workload analysis created a practical view of how model architecture, software systems, and accelerators interact. This was hardware/software co-design exposure, not deep hardware-design ownership.
Current · US · Bay Area
I work on Agentic AI platforms and cloud infrastructure, applying a systems perspective shaped by the layers below: devices, data, ML, distributed platforms, and AI infrastructure.