Małgorzata Łuczak is a distinguished Senior Staff Software Engineer at Google, based in Zürich, Switzerland, with a profound expertise in Artificial Intelligence and Machine Learning. She is a prominent figure in the tech community, particularly known for her extensive work with TensorFlow, MLOps, and building scalable ML systems. Małgorzata holds a PhD in Particle Physics from her time at CERN, which provided her with a strong foundation in large-scale data analysis and computational challenges. At Google, she focuses on developing cutting-edge ML solutions and infrastructure, contributing significantly to Google's AI capabilities. Beyond her core engineering role, Małgorzata is a passionate advocate for knowledge sharing and community building. She is a Google Developer Expert (GDE) in Machine Learning, frequently delivering insightful talks, workshops, and content aimed at demystifying complex ML concepts for developers and practitioners worldwide. Her contributions often highlight practical applications, best practices in ML model development and deployment, and the future trajectory of AI technologies.
Małgorzata Łuczak's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Recognized by Google for her exceptional expertise and contributions to the Machine Learning community, particularly with TensorFlow. She actively shares knowledge through speaking engagements, publications, and mentorship.
Holds a high-impact senior technical role at Google, leading and contributing to the development of advanced AI/ML products and infrastructure, with a focus on TensorFlow, Kubeflow, and MLOps.
Frequently invited to speak at major international technology and AI conferences such as Google I/O, TensorFlow World, KubeCon + CloudNativeCon, O'Reilly AI Conference, and various DevFests, sharing her insights on ML systems, MLOps, and TensorFlow.
Earned a doctorate with research conducted at CERN, focusing on data analysis for the CMS experiment. This experience provided a strong foundation in handling large datasets and complex computational problems, directly applicable to her work in AI/ML.
Contributes articles, blog posts, and educational content on Machine Learning, often published on platforms like Medium and Google's official blogs, making complex topics accessible to a broader audience.
University of California, Los Angeles
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