Machine Learning Engineering Manager - Content Intelligence (Violative Content Detection)

Delivering the best Spotify experience possible. To as many people as possible. In as many moments as possible. That’s what the Experience team is all about. We use our deep understanding of consumer expectations to enrich the lives of millions of our users all over the world, bringing the music and audio they love to the devices, apps and platforms they use every day. Know what our users want? Join us and help Spotify give it to them. 
The Content Intelligence organization aims for Spotify to have the most complete and correct information in the music industry.  Through a diverse set of initiatives including our content knowledge graph, human-in-the-loop, creator/content representation, and violative content detection, our squads in Content Intelligence strive to accurately model the full landscape of content at Spotify to enable a safe and trustworthy experience for our users.We are looking for a Machine Learning Engineering Manager to join our Content Intelligence product area and help drive the direction and development of proactive content moderation at scale. As a part of our team, you will work closely with machine learning research as well as partner product and engineering teams to build, to lead a team that will deploy and maintain production ML models in the Content Understanding and Moderation space. Your work will impact the experience of millions of users globally and be instrumental in keeping Spotify a safe and compliant platform where creativity can flourish.

What you’ll do

• Coordinate with Product and Engineering leadership to identify both the long-term and short-term needs in the Content Understanding space.
• Communicate complex concepts and the results of analyses in a clear and effective manner to technical and non-technical audiences.
• Lead the team in building and deploying robust ML/DL models that detect violative content and creator activity that poses a threat to Spotify’s Terms of Service.
• Collaborate with a cross-functional agile team, Content Understanding, spanning research, data science, product management, and engineering to build new product features that improve the detection of content that violates Spotify’s Terms of Service.
• Collaborate with other team members and cross-functionally to share knowledge and discuss initiatives.

Who you are

• You can draw on substantial depth and breadth of management experience to lead and grow a machine learning team.
• You have expertise in the ML Operations lifecycle; data acquisition, model training, and model deployment.
• You have expertise in full product lifecycle; technical designs, project planning, iterative implementation, and successful product launches.
• You collaborate well with teams with different backgrounds/expertise/functions.
• You care about data-driven development, reliability, and responsible experimentation.
• You understand the application of intermediate principles of data science (machine learning, statistics, computer science, mathematics) to solve technical problems.
• You have experience and passion for mentoring and encouraging collaborative teams.
• You have experience in cultivating a strong engineering culture in an agile environment.

Where you'll be

• We are a distributed workforce enabling our band members to find a work mode that is best for them!
• 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.
• Working hours? We operate within the Eastern Standard time zone for collaboration

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.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.