Jennifer Villa Email & Phone Number

New York, Ny, Us

Grafana Labs is the company behind leading open source projects Grafana, Loki, Mimir, Tempo, Pyroscope, and k6, and the creator of the first open and composable observability platform.I'm the lead product manager for Grafana Labs' core observability databases, spanning our open source, SaaS (Grafana Cloud), and Enterprise (self-hosted/on-prem) offerings.

New York, Ny, Us

New York, Ny, Us

New York, Ny, Us

At Grafana Labs, I’m the PM for Grafana Enterprise Metrics and Enterprise Logs. These products are our self-hosted solutions for customers looking for horizontally-scalable, highly-available, multi-tenant backends to store and query their metrics and logs. As a PM, I set the product vision, prioritize our backlog, collaborate with engineering to scope feature development, and support sales enablement.

San Francisco, California, Us

As a senior product operations manager at Cruise, I focused on accelerating the pace with which we could develop and deploy ML-models. I served as the product lead for our Ground Truth Automation team, where we developed ML-powered automation features to increase LiDAR data labeling efficiency. In this role, I authored the product strategy, collaborated with Design and Engineering to define an implementation plan, ran A/B tests to assess feature impact, and managed the production rollout. More recently, I was the product lead for visualizing AV on-road performance metrics. I launched a new metrics reporting app to improve the user experience and better integrate with existing AV-engineering workflows. To improve the reliability with which we report those metrics, I drove adoption of SLAs, on-call processes, and monitoring for all stages of the metrics pipeline, decreasing end-to-end system latency by 46%.

Houston, Texas, Us

Determined AI is a ML-infrastructure company focused on decreasing the time and effort it takes to train deep learning models today. Determined accelerates the model development workflow by providing out-of-the-box support for distributed training, hyperparameter tuning, and experiment sharing and reproducibility. While interning at the company, I interviewed prospective customers to understand pain points in the model development lifecycle, using this to prioritize features in the product roadmap. I also did competitive analysis, developing a framework to highlight how the company should position itself relative to competitors in the ML infra-space. Finally, I authored marketing materials (blog posts, sales collateral, pitch deck slides) to establish the company as an authority in deep learning and illustrate its value proposition to prospects.

Santa Clara, California, Us

As a software engineering intern in Intel’s Software and Services group, I analyzed efficiency tradeoffs among various techniques for compressing convolutional neural networks (CNNs) to enable their deployment in embedded systems. I designed and ran experiments in Tensorflow to quantify the accuracy impact of running inference in floating point versus integer precision in popular CNNs (VGG16, ResNet, GoogLeNet, and Mobilenet).

Santa Clara, California, Us

I worked as a CPU Performance engineer on Atom, Intel’s low-power microprocessor. I modeled changes to our hardware architecture in a C++ based, cycle-accurate software model, and then analyzed and quantified the performance impact on various computing benchmarks. I also worked to ensure performance correlation between our hardware and the software model, identifying and fixing simulator bugs as well as escalating hardware performance issues to the RTL design team. I led the development of a CPU power estimation model that leveraged our performance estimation model, consolidating input from design, architecture and power teams. Our final model met its goal of projecting 90% of workloads within 5%.

As part of Duke’s Pratt Fellows program, I worked as a research assistant in Dr. Marc Sommer’s Biomedical Engineering lab. I collaborated in the design of a Python-based computational neural network that mimicked the human-visual motor system and ran experiments with the model to develop hypotheses about how the human brain stabilizes visual input. In my senior year, I presented my research before a faculty committee to earn graduation with distinction.

Master Of Science In Computer Science (Mscs), Concentration In Artificial Intelligence

Master Of Business Administration (Mba)

Bachelor Of Engineering (B.S.E.), Dual Major In Electrical And Computer Engineering (Ece) & Biomedical Engineering (Bme)