Engineering Manager, Machine Learning Infrastructure, Technology Platform

We are 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. Our next generation ML infrastructure needs to scale to petabytes of data while still enabling quick iteration. In this role you will primarily focus on the ML infra team, but also work closely with many of the ML teams across Spotify including ads targeting, personalization, music recommendations, content and more.  Above all, your work will impact the way the world experiences music.

What you’ll do

  • You will build and lead a team of engineers through hiring, coaching, mentoring, and hands-on career development
  • 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 the team in a number of aspects of data science, machine learning and engineering
  • You will partner with the team’s product manager 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 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 production-scale 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 Scikit-learn and Tensorflow
  • 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 strongly believe that diversity of experience, perspectives, and background will lead to a better workplace 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.

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