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Pierre L. has a diverse work experience in the field of machine learning and research. Pierre currently works as a Senior ML Engineer/Researcher at avatarin, where they focus on Imitation Learning research for the Moonshot Project. Their responsibilities include developing AI models to assist non-expert users in accomplishing remote tasks at an expert level. Pierre also works on improving data, training, and inference pipelines and integrating Nvidia AI technologies into existing applications.

Prior to their current role, Pierre worked as a Machine Learning Researcher at avatarin, where they conducted research in the field of machine learning.

Before that, Pierre gained experience as a Data Scientist at ABEJA, Inc. Pierre was responsible for tasks such as data science and data management consulting, image classification, object detection, and developing a question answering system using NLP techniques. Pierre also handled data analysis and manipulation and worked on Proof of Concept (PoC) projects for clients. Pierre mainly used Python, Tensorflow, and Pytorch for their work at ABEJA.

Pierre also has experience as an Intern Research Engineer at Inria, where they developed a Fixed Point arithmetic library and performed performance analysis on Intel and ARM processors.

Furthermore, Pierre worked as an Intern Research Engineer at Institut de Physique de Rennes - UMR CNRS 6251, where they developed Python subroutines to gather, store, and analyze data. Pierre also created a user interface to fetch and display data analysis graphs.

Overall, Pierre has a strong background in machine learning, research, and data analysis, and has contributed to various projects and research initiatives throughout their career.

Pierre L. obtained a Bachelor's degree in Music and Sound Engineering from Université Paris Est Marne la Vallée in 2014. Pierre then pursued a Bachelor's degree in Physics at Université de Rennes I from 2014 to 2017. Following this, they earned a Master's degree in Scientific Computing and Modeling from Université de Rennes I, which they completed in 2019.

In addition to their formal education, Pierre also obtained several certifications in machine learning. In September 2019, they obtained certifications in "End-to-End Machine Learning with TensorFlow on GCP," "Google Cloud Platform Big Data and Machine Learning Fundamentals," "How Google Does Machine Learning," and "Launching into Machine Learning," all from Coursera.