Noam Yizraeli Email & Phone Number

Tel Aviv District, Israel

I worked within a cross-functional team consisting of Developers, QA, and team-specific DevOps personnel. Initially, my focus was on improving process stability and recoverability. Collaborating with a team member, I refactored existing system actions to enhance idempotency and efficiency.During this time, I identified inefficiencies in the process of code reaching the "master" branch from feature branches. To address this, I made several improvements:• Enhanced the Jenkins pipeline by introducing parallelism and caching where possible, significantly speeding up the CI/CD process.• Integrated static code analysis to streamline code reviews and reduce back-and-forth discussions about style issues.• Established a unified code format, helping the team adopt a consistent style and minimizing conflicts related to code aesthetics.In the latter half of my role, I focused on enhancing process stability across multiple microservices and led a major optimization and load-handling project. Key areas of the system were underperforming or crashing during heavy tasks. I optimized various components using profilers, a data-driven approach, and extensive `explain analyze` I might add, enabling the handling and saving of millions of records synchronously (via requests or files) and asynchronously (via Kafka). Initially, the process took several days due to user wait times at each step, but my optimizations reduced this to mere minutes. This transformation improved the system’s reputation and opened up new growth opportunities.As part of the optimization project, I noticed distributed tracing and other features existing in newer versions of Spring Boot thus starting a year-long process of migrating most of our actively worked-on stack from Spring Boot 2.0.X to 3.2.X, the change from an initial not production-ready release fixed lots of stability and security bugs along the way helping the system's reputation and allowing more risk for bigger projects

Israel

As a full-stack engineer with a strong focus on infrastructure and technical product lifecycle, I have a track record of delivering impactful solutions that enhance workflows and improve system reliability,• Developed a web application to streamline and automate daily developer workflows, using React and Python with Flask iterated over solutions to bring fast MVPs to focus on value. Integrated Kubernetes sidecars for enhanced functionality and scalability of our developer's apps.• Centralized organizational tools and resources into a single, authenticated portal, reducing operational overhead and improving team productivity.• Gained valuable experience in system design, leveraging insights into developer workflows to optimize user experience and efficiency.• Enhanced observability by creating a custom status check script, automating fault detection, and reducing disaster recovery times by 89%, while increasing the uptime of legacy systems to 98.5% and our newer stack to 99.9%.• Leveraged the Prometheus stack to implement tailored exporters, enabling proactive infrastructure monitoring and management.• Introduced Kubernetes best practices, including optimized resource limits, improving cluster uptime from 87% to 99.9%, and stabilizing systems during major releases.• Provided strategic guidance on Docker image optimization, resource limits, and system architecture, tailored to different software languages.

I participated in the "CS, Academy and Industry" program at the Davidson Wing of the Weizmann Institute. During the first year, I attended lectures from industry experts on various cutting-edge topics, including bio-computing, Deep Learning, and computer vision along with basic ones like computer architecture over time, which gave me deep insights into various technological advancements.In the second year, under the mentorship of Dr. Ran Califa, I focused on computer vision, linear algebra, and image processing, while honing my matrix-based programming skills in MATLAB. I developed a two-stage project called Road Guardian, designed to process dashcam footage and eventually achieved near real-time performance. The system could detect vehicles, calculate their distance from the driver's car, and issue alerts for sudden accelerations of the front vehicle. I later enhanced the project by adding a lane diversion alert, which factored in both the car’s distance from the lane center and the driver's intent based on acceleration.The program achieved high accuracy and resiliency under varying conditions (different car types and times of day). It was highly regarded by my mentors and peers, earning me the opportunity to present the project to the entire class.

Bachelor Of Science - Bs, Computer Science

Computer Science

Computer Science And Physics