$ cat jobs/senior-member-technical-staff-thenielsencompany-300a3b9062bb.json
Senior Member Technical Staff
At Nielsen, we are passionate about powering a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future. Gracenote is the content business unit of Nielsen that powers the world of media entertainment. Our metadata solutions help media and entertainment companies around the world deliver personalized content search and discovery, connecting audiences with the content they love. We’re at the intersection of people and media entertainment. With our cutting-edge technology and solutions, we help audiences easily find TV shows, movies, music and sports across multiple platforms. As the world leader in entertainment data and services, we power the world’s top streaming platforms, cable and satellite TV providers, media companies, consumer electronics manufacturers, music services and automakers to navigate and succeed in the competitive streaming world. Our metadata entertainment solutions have a global footprint of 80+ countries, 100K+ channels and catalogs, 70+ sports and 100M+ music tracks, all across 35 languages We are hiring a highly motivated Lead Machine Learning Engineer to build and scale production ML systems across text and image modalities. This is a hands-on individual contributor role for someone who can independently design and ship robust inference backends, automate training and deployment workflows, and improve model performance across both traditional ML and modern deep learning systems. You will work to productionize models r
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