Minimum Requirements Strong candidates will have graduate studies in Computer Science, Applied Mathematics, or the equivalent (or in the life sciences with a focus on machine learning techniques) and 2+ years of industry experience building machine learning powered tools. 4+ years of industry experience in machine learning engineering. Graduate studies in Computer Science, Applied Mathematics, or Life Sciences with a focus on AI/ML techniques, or undergraduate studies in Computer Science and equivalent work history. Experienced in software engineering with advanced skills in Python and/or C++. Experience in PyTorch, TensorFlow, or other deep learning frameworks. Breadth across the ML stack, and depth in at least one discipline. Experience with shipping products powered by machine learning. Academic or industry experience in the biomedical sciences especially genetics, molecular biology, or AI driven drug discovery. Understanding and application of best practices in machine learning, software engineering, and/or production deployment of ML services. Understanding of modern ML Architectures, Platforms, and backend systems. Mentality of commit early and often, metrics before models, and shipping high quality production code. Track record of contributing to open source projects. Responsibilities A senior engineer can consistently take a poorly defined problem and formulate clear objectives, then execute on it to build a high performing product or service. They are the model for the team in terms of code quality, standards, and best practices, and they act as mentors to junior members of the team. Company information: We are uniting science, technology and talent to get ahead of disease together. #J-18808-Ljbffr GSK
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