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Staff Engineer for Spotify's Experience Team
11 hours ago
The way people consume music and audio is constantly evolving, driven by technological advancements and changing user behaviors. At Spotify, we're committed to delivering the best possible user experience in every moment, leveraging our deep understanding of consumer expectations to create value for our users and our business.
Job Description:The Content and Catalog Management (CoCaM) team sits at the heart of the Content Platform R&D studio, playing a vital role in managing content and informing decisions that impact the entire organization on content appropriateness, availability, quality, and accuracy. This involves combining reactive and proactive reporting mechanisms with knowledge of the Content Platform and business policies, using content, user, financial, and experiential context to make informed decisions best for creators, consumers, and Spotify.
We're looking for a skilled Machine Learning (ML) Staff Engineer to own the definition, adoption, and expansion of ML usage within our content and catalogue management platform. As part of our community of engineers, researchers, product managers, designers, and data scientists, you'll collaborate to expand CoCaM ML knowledge and expertise, identifying opportunities for more efficient, effective, and consistent ML use in our decision-making pipeline.
Key Responsibilities:- 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.
- 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.
- 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.
- 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.
- Promote experimentation and iteration to encourage out-of-the-box approaches to engineering problems, balancing the need to deliver outcomes and goals.
- Drive technical decisions and standard methodologies in ML to ensure high-quality and scalable solutions are built by our engineers.
- 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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