Experienced Machine Learning Engineer – Growth (Automated Marketing) 674 views

The Automated Marketing team uses technology to communicate the value of Spotify to a global audience, so billions of people can enjoy and support the creative work of millions of artists. There are so many features that people love about Spotify: discovering new music, following favorite artists, enjoying podcasts, finding concerts, and more. They build the tools and systems that help their users discover the many aspects of Spotify, and they use data and machine learning to find the best ways to advertise Spotify’s outstanding value to new audiences.

Within the Automated Marketing team, they work in high-performance, cross-functional teams. Their design, engineering, and data science practitioners build new user experiences and experiments, and when they find new insights, they incorporate them into their production ML models to optimize the operations and cost of their global marketing presence. Their work has high visibility within the consumer experience and directly contributes to Spotify’s top and bottom lines.

What You’ll Do

• • Work with a high-performance, cross-functional team whose mission is to engage users and communicate the many value propositions of Spotify to each user, from their favorite artist’s new album to new music discovery, from keeping up with favorite podcasts, to finding live performances, and more.
  • Work at the intersection of engineering and marketing, crafting automated and optimized marketing systems to operate a best-in-class business that grows Spotify’s global user base.
  • Train models and evaluate their effectiveness against metrics that encapsulate real and immediate business objectives.
  • Drive tooling and infrastructure improvements for cloud-based ML deployments
  • Apply techniques and methods from literature to business operations that require forecasting, classification, ranking, and A/B/N testing.

Who You Are

• • You have strong hands-on industry experience implementing and maintaining high-scale, production ML systems.
  • You are comfortable explaining the intuition and assumptions behind ML and mathematical concepts, and you can creatively apply these concepts to design ML systems to tackle challenging problems. You can explain and discuss pros and cons of learning regimes, and identify scenarios in which one might best apply.
  • You are experienced with crafting data pipelines, and you are self-sufficient in driving the process of designing features, labeling training data, and evaluating models.
  • You care about agile software processes, data-driven development, reliability, and focused experimentation
  • You are passionate about learning and sharing in an early-stage team environment.
  • You love your customers even more than your code

Plus/bonus

• • Experience with TensorFlow.
  • Experience in causal inference or methods related to customer lifetime value
  • Experience with applying deep learning techniques for ranking, content affinity, sequential modeling, or natural language processing in production
  • Experience with high-scale, distributed data processing frameworks like Beam or Spark

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. Their platform is for everyone, and so is their workplace. The more voices they have represented and amplified in our business, the more they will all thrive, contribute and be brilliant. So bring them your personal experience, your perspectives, and your background. It’s in their differences that they will find the power to keep revolutionizing the way the world listens.

Spotify transformed music listening forever when we launched in 2008. Their 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 opportunity to enjoy and be inspired by these creators. Everything they do is driven by their love for music and podcasting. Today, they are the world’s most popular audio streaming subscription service with a community of more than 299 million users.