About

Andrés Pipicello is a highly experienced Principal Machine Learning Engineer with over 15 years of relevant experience in the industry. Currently working at asapp as a Senior Staff Machine Learning Engineer, he is responsible for representing the ML Team on cross-company concerns, coaching his juniors, and advocating for constant CD and CD improvement. He is also a referent of Docker, Kubernetes, AWS, and Terraform. Throughout his career, Andrés has worked on various projects, including designing and implementing a compatibility layer for multitenancy setups, allowing for multitenancy-oblivious ML services to work on MT environments. He has also worked with members from the Research team in the evaluation of the feasibility of introducing ONNX and GraalVM for model serving and produced an architectonic vision for the introduction of ONNX as a serving technology. Prior to his current role, Andrés worked at OLX as a Principal Machine Learning Engineer, where he was responsible for the performance, stability, and other non-functional requirements of the Personalization and Relevance team's machine learning models. He also introduced new technologies to the team, such as Apache Spark and Scala. Some of the projects he worked on at OLX include designing a big data architecture for the training and serving of an ML-based ranking service for searches, applying the word2vec principles to create an embedding of user searches and items, and aligning the usage and consumption of data sources in compliance with GDPR. Andrés holds a degree in Information Systems Engineering from the Universidad Tecnológica Nacional, which he earned in 2006. He has a diverse tech stack that includes ML, P2P, AWS, Terraform, Kubernetes, Docker, Research Scientist, Word2Vec, Spark, CI/CD, Big Data, Scala, and Software Engineer. He is a highly skilled engineer with an excellent track record of delivering results and exceeding expectations.