Everyday, hundreds of millions of people all over the world use Spotify to discover and listen to music and podcasts. We seek to understand the world of audio better than anyone else so that we can make great recommendations to every individual and keep the world listening. The product includes highly personalised surfaces as well as original playlists such as “Discover Weekly” and “Daily Mix”, all powered by some of the most advanced machine learning algorithms in the audio space.
To enable this and all other teams in the ML space including ads, content and more, the ML platform team owns and maintains the infrastructure and the strategy for the platform on top of which machine learning is done at Spotify. We are now looking for an Engineering Manager to help us define and build the next generation of ML infrastructure at Spotify. The role is to manage a growing team of engineers with the mission to enable every team at Spotify to apply ML to their business problems and iterate quickly on hypotheses.
What you’ll do
- You will hire, coach, mentor and develop the careers of a team of engineers
- You’ll be responsible for building upon Spotify’s suite of tools for developing and delivering production-scale end-to-end Machine Learning workflows
- You will provide guidance and collaborate with Spotify teams in a number of aspects of data science, machine learning and engineering
- You will partner with the team’s product managers and EMs to engage with various Spotify product teams to: understand their changing needs in the ML space, evangelize our ML infrastructure and products, jointly plan and prioritize high-level cross-team collaborations.
- You will support the engineering team in formulating the technical strategy for evaluation and adoption of open source and third party ML infrastructure solutions
- In the end, your primary goal is to grow a highly effective engineering team
Who you are
- You thrive when developing great people, not just great products
- You have experience in cultivating a strong engineering culture in an agile environment
- You have previous experience developing large scale production ML systems
- You are either an experienced manager or a senior individual contributor with strong people skills and leadership experience
- You have previous industry experience with large scale ML systems using frameworks such as Tensorflow, Scikit-learn and XGBoost
- You care about agile software processes, data-driven development, reliability, and responsible experimentation
- You’re familiar with the industry trends and keep up with the latest product offerings, and can understand trade-offs of existing solutions
- Ideally you’re actively engaged in the ML community (open source, meetups)
We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.