Machine Learning Engineer for Content Platform

18 hours ago


Stockholm, Stockholm, Sweden TN Sweden Full time

Delivering exceptional user experiences is at the heart of what we do. Our Experience team uses its deep understanding of consumer expectations to enrich the lives of millions of users worldwide. We bring music and audio to the devices, apps, and platforms people use every day.

Job Description:

The Content and Catalog Management (CoCaM) team plays a critical role in the Content Platform R&D studio, driving the management of content and making decisions that impact the entire organization on content appropriateness, availability, quality, and accuracy. To achieve this, we rely on reactive and proactive reporting mechanisms, applying knowledge of the Content Platform and business policies with content, user, financial, and experiential context to make informed decisions best for creators, consumers, and Spotify.

We are seeking a Machine Learning (ML) Staff Engineer to own the definition, adoption, and expansion of ML usage within our content and catalogue management platform. You will work closely with engineers, researchers, product managers, designers, and data scientists with varying levels of exposure and experience in ML. Together, you will expand CoCaM ML knowledge and expertise, collaborating to identify opportunities for more efficient, effective, and consistent ML use in our decision-making pipeline.

Key Responsibilities:
  1. Develop and implement an ML strategy for content and catalog management across six squads, ensuring the platform supports diverse content types, provides data for reporting, and enables the right balance of fast and accurate decisions.
  2. Enhance the ML competence among 40+ engineers, engineering managers, and product managers, providing mentorship on ML usage with traditional engineering approaches to apply the right solution for the right problem.
  3. Partner with Staff Engineers and Product partners, policy owners, and operational teams to identify and demonstrate ML opportunities, encouraging critical thinking within teams to develop this understanding themselves.
  4. Cultivate strong relationships within the CoCaM Staff Engineers, Engineering Managers, and Product Managers, promoting a culture of collaboration, openness, and inclusion to develop well-rounded solutions.
  5. Promote experimentation and iteration to encourage out-of-the-box approaches to engineering problems, balancing the need to deliver outcomes and goals.
  6. Drive technical decisions and standard methodologies in ML to ensure high-quality and scalable solutions are built by our engineers.
  7. Stay updated with the latest ML advancements and Spotify ML standards, developing a learning environment to continuously improve the team's skills and knowledge.


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