Machine Learning Engineering Manager – Personalization

🕒 July 30

🗽 New York – Remote

🗽 New York – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👮‍♀️ Software Engineering Manager

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Spotify

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2008

📱 Media

👥 B2C

🛍️ eCommerce

Media • B2C • eCommerce

Spotify is a global audio streaming service company that offers its users access to a vast library of music and podcasts. Known for its focus on delivering personalized listening experiences, Spotify employs data scientists, engineers, and client partners across various global locations to continuously innovate and enhance its offerings. The company fosters a strong culture of diversity, equity, and impact, emphasizing belonging and inclusion in its workforce. Spotify is not only committed to shaping the future of audio entertainment but also to making a positive societal impact, with initiatives focused on social and environmental issues.

📋 Description

• Lead, coach, and develop a team of machine learning engineers, creating an inclusive, high-performing engineering culture. • Set the technical direction for the team while partnering with Product, Data Science, and Engineering leaders to deliver impactful machine learning capabilities. • Guide the design, development, deployment, and operation of production machine learning systems at scale. • Support engineers through technical mentorship, career development, performance management, and regular feedback. • Drive execution by helping the team prioritize work, remove obstacles, and continuously improve delivery. • Foster engineering excellence through modern software engineering practices, experimentation, and operational excellence. • Partner across squads and missions to influence technical strategy and ensure alignment across the Personalization organization. • Champion thoughtful adoption of emerging machine learning technologies, including large language models, where they create meaningful user value.

🎯 Requirements

• You have experience leading and developing high-performing engineering teams. • You have built trust through coaching, mentoring, and supporting engineers in their career growth. • You have deep expertise building and operating production machine learning systems at scale. • You understand the end-to-end machine learning lifecycle, from experimentation through deployment and monitoring. • You are experienced working with modern machine learning techniques, including large language models and generative AI applications. • You communicate effectively across engineering, product, and data science partners. • You care about building inclusive teams where collaboration, curiosity, and continuous learning thrive. • You balance technical excellence with pragmatic decision-making and delivering meaningful business outcomes.

🏖️ Benefits

• Flexible to work where you work best!