Edison is a team within Spotify that finds new areas of user Growth. In other words, we build to get more people using Spotify. The Edison team is looking for a Machine Learning Engineer to help them with this mission. We will use best-in-class Machine Learning to build data driven solutions. These solutions will directly provide value to the listeners of music on Spotify. We will build a smarter product that is personalized for every use case and every user. This better tuned experience will lead to more users on Spotify. In summary you will utilize Machine Learning to directly affect Spotify’s iOS and Android app which will ultimately make more people love using Spotify.
What you’ll do
- Build new or take already live features of our apps and make them better utilizing ML
- Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
- Prototype new approaches and productionize solutions at scale.
- Build systems that take in multiple user signals and suggest feature optimizations for each user.
- Take on complex data-related problems using some of the most diverse datasets available
- Perform data analysis to establish baselines and inform product decisions.
- Run experiments to understand the value of your approaches
- Collaborate with a cross-functional agile team spanning design, data science, product management and engineering.
Who you are
- You have a strong background in machine learning, data and backend.
- You have experience building data pipelines and are self-sufficient in getting the data you need to build and evaluate your models, using tools like Apache Beam / Scio.
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
- Experience with pyTorch, TensorFlow, or Google Cloud Platform is a plus.
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
- You have experience and passion for mentoring and encouraging collaborative teams.
- You love your customers even more than your code.
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.