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Position: Director - Machine Learning Engineering
Institution: Warner Bros. Discovery
Location: Bangalore, India
Duties: The role will focus on building and leading a team responsible for unlocking machine learning opportunities in media supply chain, captioning services, ad conditioning, metadata extraction and building foundational machine learning training and inference pipelines at scale. You will lead by example and define the best practices, will set high standards for the entire team and for the rest of the organization. You have a successful track record for ambitious projects across cross-functional teams. You are passionate and results oriented. You strive for technical excellence and are very hands-on. Your co-workers love working with you. You have built respect in your career through concrete accomplishments
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
   
Text: Director - Machine Learning Engineering The role will focus on building and leading a team responsible for unlocking machine learning opportunities in media supply chain, captioning services, ad conditioning, metadata extraction and building foundational machine learning training and inference pipelines at scale. You will lead by example and define the best practices, will set high standards for the entire team and for the rest of the organization. You have a successful track record for ambitious projects across cross-functional teams. You are passionate and results oriented. You strive for technical excellence and are very hands-on. Your co-workers love working with you. You have built respect in your career through concrete accomplishments 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
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