About

Lorenzo Arribas is a highly skilled Software Engineer with over a decade of experience in distributed, event-driven architectures, and Machine Learning operations. He has worked in two hyper-growth start-ups, where he witnessed their transformation into well-established multinational companies. Lorenzo is passionate about working in fast-paced environments, where he can have an impact, work with brilliant colleagues, and feel challenged every day. Currently, Lorenzo works as a Staff Software Engineer at Glovo, where he is responsible for the Data Platform. He has been involved in two major projects, including migrating their fleet of ML microservices to Kubernetes and adopting Argo Workflows for distributed training of ML models. His work has resulted in a 70% cost reduction, 99.99% availability, and double resource utilization. In his previous role as a Senior Software Engineer, Machine Learning Platform Team at Glovo, Lorenzo's focus was on reliability, observability, and cost efficiency of infrastructure. He created a platform that enabled product teams to run distributed training sessions and adopt best practices for model testing, benchmarking, continuous integration, and continuous delivery. Lorenzo's educational background includes a Bachelor's degree in Computer Science from the Universitat Politècnica de Catalunya. He is proficient in a wide range of technologies, including Kubernetes, AWS, Sagemaker, Python, Microservices, CI/CD, Jenkins, Integration, Backend, Frontend, and test. With 8.11 years of relevant experience, Lorenzo is a highly skilled Software Engineer who thrives in challenging environments and is always looking to expand his skill set.