Grey Matter
Patrick Riley has work experience in various software engineering roles. Patrick is currently working as a Software Engineer at greymatter.io since May 2022. Prior to that, they worked as a Software Engineer Co-Op at Peraton from August 2021 to December 2021. From September 2019 to December 2021, they served as an Undergraduate Research Assistant at Virginia Tech Hume Center. In 2021, they also worked as a Ford Pro Intelligence Software Engineering Intern at Ford Motor Company from May to July. Additionally, they have previous experience at greymatter.io, where they worked as a Software Engineer from May 2020 to September 2020 and as a Software Engineering Intern from June 2019 to May 2020.
Patrick Riley completed their education as follows:
From 2022 to 2024, Patrick attended Virginia Tech and obtained a Master of Engineering (MEng) degree in Computer Science.
Prior to their master's degree, they pursued a Bachelor's degree in Computer Science at Virginia Tech College of Engineering from 2019 to 2023.
In their earlier years, from 2015 to 2019, Patrick attended Bishop Ireton HS, although no specific degree or field of study is mentioned.
Additionally, in April 2017, Patrick obtained a certification as a Motor Boat Operator (To Carry Passengers) from the BoatUS Foundation.
Grey Matter
Grey Matter is an intelligent mesh platform for enterprise microservice, container, and hybrid cloud operations and management. Our focus on enabling enterprise governance, risk and compliance by leveraging the service mesh technologies for the development to day 2 AI Ops lifecycle. Our platform delivers reliable secure networkperformance, service level management and business intelligence, resource control, automation, and cost efficiency for the enterprise. Grey Matter is a pathway to enterprise modernization and cost control, providing interlacing service control, data management, and neural net functions designed to optimize enterprise distributed systems ROI and TCO.Grey Matter facilitates the management of distributed microservice workloads, controls network traffic, and smartly scales infrastructure to meet business demands. The capture and analysis of over 100 telemetry types powers onboard service level management and control. Our customers rely on Grey Matter’s speed, security, and reliability for critical distributed cloud management and data discovery, storage, and global sharing requirements. An industrial AI software pathway to intent-based networking and AIOps, the platform is also designed to optimize enterprise network availability and performance through AI neural network analysis, enabling AIOps for contextual awareness and intelligent network monitoring.