Kyle Nesbit Email & Phone Number

Denver, Co, Us

Mountain View, Ca, Us

I am tech lead for a team of engineers focused on leveraging AI to improve Google Cloud's business intelligence and data analytics product suite. See examples linked below.I also led the integration of Looker into Google Cloud Platform (i.e., Looker Core). Looker is a data exploration and discovery business intelligence platform. Looker was acquired by Google in 2020.

Mountain View, Ca, Us

Gradient Ventures is Google’s AI-focused venture firm, which invests in and connects early stage startups with Google’s resources, innovation, and technical leadership in AI.I ran Gradient's residency program and drove Gradient 's data stack strategy. I worked with founders on engineering development and recruited top AI talent to work with Gradient's portfolio companies. In some portfolio company engagements, I was fully embedded, rolled up my sleeves, wrote code, built ML models, devop'd, fought fires, and shipped features & products. For example see Labelbox's assisted labeling feature and UnitQ's LLM-based products referenced below.I also performed market research, technical diligence on deals, was a board observer, and provided technical direction to Gradient's portfolio companies.

Mountain View, Ca, Us

I led a team of engineers and researchers developing machine learning and statistical models to measure the efficacy of Google ads. My team and I built human sensing computer vision models to measure consumer engagement with digital ads and models to extract offline sales data from photographed receipts. For example, see the human pose estimation and receipt scanning projects referenced below.

Mountain View, Ca, Us

I led a team of software and site reliability engineers in designing, developing, and deploying one of Google's most advanced distributed storage systems. The system was built for high-performance applications -- applications that demand ultra low latency and very high throughput. It stores data in-memory and leverages Google's advanced network technologies to achieve the best performance possible. The system is now deployed widely at Google and backs multiple mission critical products. Some examples include Google's BigQuery and Cloud Dataflow cloud offerrings. See articles linked below.I have 9 patents in the area of high-performance distributed storage based on this work. Including the seminal work on "Single-Sided Distributed Storage Systems". See links below.

Madison, Wi, Us

Researched microarchitectural resource sharing in chip multiprocessor systems. Proposed and published novel techniques to control microarchitectural resource sharing in order to provide QoS and fairness. Proposed and published novel cache prefetching techniques. The results of my research were published in multiple top-tier computer architecture conferences. See link below.

Santa Clara, California, Us

Developed performance models for Intel's next generation Itanium processors.

Armonk, New York, Ny, Us

Developed a microprocessor modeling framework based on SystemC. Developed multiprocessor performance models of IBMs zSeries (mainframe) servers.Floating point logic design and verification for IBM's Power4, Power5, and Cell (Playstation 3) microprocessors.