Experienced Machine Learning Engineer – Growth


New York City, NY, US
  • Job Type: Full-Time
  • Function: Data Science
  • Post Date: 01/17/2021
  • Website: spotify.com
  • Company Address: Birger Jarlsgatan 61, Stockholm, 114 34

About Spotify

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 opportunity to enjoy and be inspired by it.

Job Description

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. We build the tools and systems that help our users discover the many aspects of Spotify, and we use data and machine learning to find the best ways to advertise Spotify’s outstanding value to new audiences.

Within the Automated Marketing team, we work in high-performance, cross-functional teams. Our design, engineering, and data science practitioners build new user experiences and experiments, and when we find new insights, we incorporate them into our production ML models to optimize the operations and cost of our global marketing presence. Our 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


    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

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Disclaimer: Local Candidates Only
This company does NOT accept candidates from outside recruiting firms. Agency contacts are not welcome.