Machine Learning Engineering Manager - Amplify

Spotify
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Job Description

We are seeking a passionate Engineering Manager with deep machine learning expertise and strong leadership skills to lead a team that predicts advertiser outcomes – a central piece of Spotify’s ad strategy. We ask that our team members are both capable and willing to work within the Eastern Standard/Daylight time zones during our collaborative hours.

What You'll Do

  • Lead, mentor, and nurture a team of highly skilled Machine Learning Engineers, fostering a positive and productive work environment.
  • Provide technical guidance in machine learning, helping each engineer find the best direction for their work, spotting lurking problems, highlighting promising directions, and focusing the team’s efforts where they are most likely to succeed
  • Collaborate closely with Product counterparts to drive effective leadership and align our efforts with the broader group's goals.
  • Learn and use knowledge of the ad industry to expand your influence and vision beyond our immediate team
  • Contribute to the development of the technical vision and strategy for the machine learning systems powering our free product, which boasts over 300 million monthly active users.
  • Inspire, manage and lead the engineering culture of our group, so we can achieve our mission

Who You Are

  • You have PhD level expertise in a quantitative field and excitement about machine learning
  • You can draw on substantial depth and breadth of management experience to lead and grow a machine learning team
  • You have experience and passion for mentoring and encouraging collaborative teams and drawing out contributions from a variety of team members
  • You are continuously curious and learning as a leader
  • You care about data-driven development, reliability, and responsible experimentation
  • You’re familiar with the industry trends and can understand trade-offs of existing solutions
  • Ad domain expertise is a plus

Where You'll Be

  • We are a distributed workforce enabling our band members to find a work mode that is best for them!
  • Where in the world? For this role, it can be within the US region in which we have a work location and is within working hours.
  • Working hours? We operate within the Eastern US time zones for collaboration and ask that all be located in that time zone.
  • Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.

The United States base range for this position is $170,000 - $243,000, plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(K) retirement plan, 23 paid days off, 13 paid flexible holidays, paid sick leave.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.

Company Info.

Spotify

Spotify is a popular digital music streaming platform that was launched in 2008. It provides users with access to a vast library of music from various genres and artists around the world. Initially, Spotify started as a desktop application but has since expanded to include mobile and web-based versions as well. Key features of Spotify include: Music Catalog, Personalized Recommendations, Social Integration, Podcasts and Audio Content and Offline

  • Industry
    Media,Entertainment
  • No. of Employees
    8,391
  • Location
    New York, NY, USA
  • Website
  • Jobs Posted

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Spotify is currently hiring Machine Learning Manager Jobs in New York, NY, USA with average base salary of $170,000 - $243,000 / Year.

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