FAQs
What is the role of a Machine Learning Engineer II on the Personalization team?
The Machine Learning Engineer II will contribute to designing, building, evaluating, shipping, and refining Spotify’s personalization products, collaborating with a cross-functional agile team to enhance user experience through recommendation algorithms.
What qualifications are required for this position?
Candidates should have a strong background in machine learning, experience with bandit algorithms and neural networks, and hands-on experience implementing production ML systems with programming languages such as Java, Scala, or Python.
What kind of experience is preferred for this role?
Preferred experience includes working with large-scale distributed data processing frameworks like Apache Beam or Apache Spark, as well as familiarity with cloud platforms such as GCP or AWS.
What tools and frameworks should a candidate be familiar with?
Candidates should be familiar with tools and frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with agile software processes and data-driven development.
What does the collaboration process look like within the team?
The team collaborates in a cross-functional environment that includes user research, design, data science, product management, and engineering to build new product features.
Where can I work if I join the team?
You can work remotely within the European region, as long as a work location is established, and collaboration will occur mainly within the GMT/CET time zone.
Does Spotify provide support for diverse candidates during recruitment?
Yes, Spotify is passionate about inclusivity and ensures that their recruitment process is accessible. Candidates can request reasonable accommodations during the interview process.
What values does Spotify prioritize in its workplace culture?
Spotify values diversity, inclusivity, and believes that a variety of perspectives will strengthen their business and contribute to innovation in the music and podcasting industry.