Baruch Gueta
Tel Aviv District,Israel
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Baruch Gueta is a highly experienced Staff Software Engineer and Tech Lead, currently at Google, with a strong focus on build systems, developer productivity, and open-source software. He is known for his deep technical expertise, particularly with Bazel, and his ability to lead complex engineering projects. Baruch is passionate about improving software development processes and is an active contributor to the tech community through speaking engagements and online content.
Professional Summary
Baruch Gueta's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Notable Achievements
Core Contributor and Tech Lead for Bazel
Played a pivotal role in the development and adoption of Bazel, Google's open-source build and test tool. Led initiatives to enhance its performance, scalability, and feature set, impacting developer productivity globally.
Public Speaker and Community Advocate
Frequently presents at international conferences (such as BazelCon, KubeCon) and local meetups, sharing insights on build systems, software engineering best practices, and developer tooling. Actively engages with the open-source community.
Innovator in Developer Productivity Tools
Led and contributed to various projects aimed at improving the developer experience and efficiency for large-scale software development, including advancements in build caching, remote execution, and dependency management.
Author and Content Creator
Shares knowledge and expertise through technical blog posts and articles, primarily on platforms like Medium, contributing to the broader understanding of complex software engineering topics.
Educational Background
Business, Management, Marketing, and Related Support Services
The Open University of Israel - Year 2009
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Company Overview
RoadSense Advanced TechnologiesRoadSense Advanced Technologies specializes in AI-powered solutions for road safety and traffic management. Their technology utilizes computer vision and deep learning algorithms to analyze road conditions, detect hazards, monitor traffic flow, and provide real-time alerts to prevent accidents and improve urban mobility. Their systems aim to make roads safer for drivers, pedestrians, and cyclists, contributing to smarter and more efficient city infrastructures.
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