$ cat jobs/senior-ai-engineer-videoai-linkedin3-fad5c60730f0.json
Senior AI Engineer, VideoAI
LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works. This role will be based in New York or Mountain View, CA. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. The Video AI team sits at the heart of our LinkedIn’s ambitious growth strategy. Our team is a dynamic group of machine learning experts dedicated to revolutionizing the way we interact with video content. This team is at the forefront of developing cutting-edge artificial intelligence technologies that enhance video understanding, search, and personalization. By leveraging state-of-the-art AI techniques, the Video AI team is poised to open up new ways of engaging with videos on LinkedIn. Our work encompasses a range of applications, from real-time video analytics to intelligent content recommendation systems, positioning our company as a leader in the rapidly evolving landscape of video technology. As LinkedIn continues to revolutionize our market presence, the Video AI team’s expertise will be instrumental in shaping our product offerings and achieving our strategic goals, ensuring we stay ahead of the competition and deliver unparalleled value to our 1 billion+ global users. Below are a few examples of the problem spaces we work in (and much
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