Optimize and deploy state-of-the-art deep learning models for protein sequences and structures; Develop efficient, high-quality code and data pipelines; Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings; Establish automated processes to continuously evaluate and improve our protein design methodology; Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company
Requirements:
MS or PhD in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field; 2+ years of industry experience in machine learning infrastructure, pipeline building, distributed training, and deployment; Demonstrated ability in re-implementation of multiple state-of-the-art models from research for comparative analysis
Text:
Machine Learning Engineer Optimize and deploy state-of-the-art deep learning models for protein sequences and structures; Develop efficient, high-quality code and data pipelines; Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings; Establish automated processes to continuously evaluate and improve our protein design methodology; Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company MS or PhD in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field; 2+ years of industry experience in machine learning infrastructure, pipeline building, distributed training, and deployment; Demonstrated ability in re-implementation of multiple state-of-the-art models from research for comparative analysis
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