Machine Learning Engineering Manager

Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Data Engineering · Software Engineering

In short

Lead and mentor a multidisciplinary team of machine learning, data, and backend engineers building core ML systems for music experiences at Spotify. This role requires strong technical depth in machine learning, the ability to assess technical tradeoffs, and skills in people management to empower experienced engineers while providing guidance and fostering a high-performing, inclusive environment.

Responsibilities

Lead, coach, and develop a multidisciplinary team of ML, data, and backend engineers.
Provide technical leadership on complex ML systems, engaging deeply with modeling strategy and implementation.
Represent and advocate for the team with cross-functional stakeholders.
Empower engineers to own technical decisions, but provide direction when needed.
Filter requests from cross-functional partners and preserve team focus.
Own healthy delivery, including prioritization, capacity management, and operational health.
Act as a player-coach, contributing hands-on to technical problem solving.
Help the team use AI effectively in engineering workflows and identify opportunities for AI improvement.
Hire and onboard engineers as the team evolves.

Requirements

Experience managing engineers and a demonstrated track record of developing and managing technical ICs.
Solid background in machine learning with credibility in modeling strategy, ML system design, and technical discussions.
Ability to independently assess ML strategies and technical tradeoffs.
Comfort operating in an environment with evolving product and business needs.
Ability to build trust with experienced engineers by giving them autonomy while remaining close enough to coach effectively.
Thoughtful leadership, knowing when to facilitate, let the team decide, or make the decision yourself.
Preference for lightweight, purposeful processes over process for its own sake.
Comfort making calculated tradeoffs and learning through iteration.
Ability to manage substantial technical, product, and business dependencies with partner teams.
Comfort using AI tools and having a point of view on AI's impact on engineering effectiveness.
Value healthy disagreement, clear ownership, accountability, and an inclusive environment.

Desired Qualifications

Experience with data engineering and backend is a plus.

Benefits

Flexibility to work where you work best within the North America region.
Collaboration across the Eastern time zone.
Base range of $184,049 - 262,928 plus equity.
Health insurance.
Six months paid parental leave.
401(k) retirement plan.
Monthly meal allowance.
23 paid days off.
13 paid flexible holidays.
Extensive learning opportunities through our dedicated team, GreenHouse.
Flexible share incentives.
Global parental leave (six months off for all new parents).
All The Feels, our employee assistance program and self-care hub.
Flexible public holidays.

Skills

machine learningdata engineeringbackend

#machine learning#data#backend#engineering leadership

About Spotify

Our mission is to unlock the potential of human creativity—by giving a million creative artists the opportunity to live off their art and billions of fans the opportunity to enjoy and be inspired by it. Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 70m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience. Today, Spotify is the most popular global audio streaming service with 365m users, including 165m subscribers…

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