Responsible for machine learning and data science development for IDC; Recruit and build out teams for applied machine learning org; Build cutting-edge capabilities utilizing machine learning and data science (e.g., large language models, computer vision models, advanced ad & content targeting, etc.); Mentor, guide, coach, coordinate training opportunities and support individual growth and technical skills across the engineering teams; Enable continuous learning environment to keep abreast of industry trends. Partner with research organizations and explore innovation opportunities; Leverage industry best practices and tools to continually improve teams' ability to build, operate and maintain products
Requirements:
PhD or master’s in computer science or related discipline; 18+ years of experience managing Machine Learning teams; years of experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed machine learning algorithms and systems; Proficiency in operating machine learning solutions at scale, covering the end-to-end ML workflow
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Director - Machine Learning Engineering Responsible for machine learning and data science development for IDC; Recruit and build out teams for applied machine learning org; Build cutting-edge capabilities utilizing machine learning and data science (e.g., large language models, computer vision models, advanced ad & content targeting, etc.); Mentor, guide, coach, coordinate training opportunities and support individual growth and technical skills across the engineering teams; Enable continuous learning environment to keep abreast of industry trends. Partner with research organizations and explore innovation opportunities; Leverage industry best practices and tools to continually improve teams' ability to build, operate and maintain products PhD or master’s in computer science or related discipline; 18+ years of experience managing Machine Learning teams; years of experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed machine learning algorithms and systems; Proficiency in operating machine learning solutions at scale, covering the end-to-end ML workflow
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