Machine Learning Engineering Manager - Music

Spotify is a music streaming company seeking an Engineering Manager to lead the Oasis Squad. The role manages a multidisciplinary team of machine learning, data, and backend engineers while providing technical leadership on ML systems, supporting delivery, and representing the team with cross-functional stakeholders.

Responsibilities:

• Lead, coach, and develop a multidisciplinary team of ML, data, and backend engineers, giving experienced ICs meaningful autonomy while providing active mentorship and coaching where needed
• Provide technical leadership on complex ML systems, engaging deeply enough with modeling strategy and implementation to challenge assumptions, assess tradeoffs, identify risks, and help the team make decisions
• Represent and advocate for the team with cross-functional stakeholders across business, product, insights, and the personalization mission, balancing technical concerns with business needs
• Empower engineers to own technical decisions, but recognize when the team needs you to provide direction, resolve a tradeoff, or make the decision yourself
• Be the point of contact for requests from cross-functional partners, filtering the important updates to the team and preserving their heads down time
• Own healthy delivery, including prioritization, capacity management, operational health, and reliable execution, while favoring lightweight processes that help the team move quickly and learn
• Stay close to the engineering craft and act as a player-coach when useful, including contributing hands-on to technical problem solving and engineering work
• Help the team use AI effectively in engineering workflows and identify opportunities for AI to improve both how we build and the ML systems we create
• Hire and onboard engineers as the team evolves, building the capabilities and knowledge distribution needed for the team to remain resilient over time

Requirements:

• Experience managing engineers and a demonstrated track record of developing and managing technical ICs
• You have a solid background in machine learning and can engage credibly in modeling strategy, ML system design, and technical discussions with experienced ML practitioners
• You can independently assess ML strategies and technical tradeoffs, challenge assumptions, and clearly represent a technical direction with both technical and non-technical stakeholders
• You are comfortable operating in an environment where technical strategy must account for evolving product and business needs, and can create clarity for your team through sudden shifts in direction
• You build trust with experienced engineers by giving them autonomy and avoiding unnecessary oversight, while remaining close enough to their work to coach effectively, understand risks, and step in when needed
• You view yourself as your team's advocate
• You are a thoughtful leader who knows when to facilitate a decision, when to let the team decide, and when to make the decision yourself
• You favor lightweight, purposeful processes over process for its own sake. You can maintain a strong understanding of work, risks, and delivery without creating unnecessary overhead for the team
• You are comfortable making calculated tradeoffs, learning through iteration, and helping teams move quickly while maintaining appropriate technical and operational standards
• You can manage substantial technical, product, and business dependencies with partner teams and build credibility with senior cross-functional stakeholders
• You are comfortable using AI tools and have a point of view on how AI can improve engineering effectiveness and evolve ML-powered products
• You value healthy disagreement, clear ownership, accountability, and an inclusive environment where people can do their best work
• Experience with data engineering and backend is a plus