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Technical Lead for Content and Catalog Engineering
2 days ago
Unlock the Power of Data-Driven Decisions
As a Staff Machine Learning Engineer in our Content and Catalog Management (CoCaM) team, you will be responsible for driving the development and implementation of cutting-edge machine learning strategies that enhance the Spotify experience.
We are looking for an experienced technical leader who can drive ML strategy across six squads, ensuring the platform can support diverse content types, policies, and data-driven decision-making. You will also be responsible for enhancing the ML competence among engineers, engineering managers, and product managers through mentorship and training.
Main Responsibilities:
- ML Strategy Development: Own the ML strategy for content and catalog management, partnering with cross-functional teams to identify and demonstrate ML opportunities.
- Mentorship and Training: Enhance the ML competence among 40+ engineers, engineering managers, and product managers, providing hands-on guidance on ML adoption.
- Culture Building: Cultivate strong relationships within the CoCaM team, promoting collaboration, openness, and inclusion to drive well-rounded solutions.
- Experimentation and Iteration: Encourage experimentation and iteration to develop out-of-the-box approaches to engineering problems.
- Technical Decision Making: Drive technical decisions and standard methodologies in ML, ensuring high-quality and scalable solutions.
- Staying Up-to-Date: Stay updated with the latest ML advancements and Spotify ML standards, developing a learning environment to continuously improve the team's skills and knowledge.
Requirements:
- Proven Track Record: Proven track record of creating, promoting, and growing ML strategy for platforms, delivering horizontal solutions to vertical problems.
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