Machine Learning Engineering Manager – Music

🔥 32 minutes ago

🗽 New York – Remote

🗽 New York – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👮‍♀️ Software Engineering Manager

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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 multidisciplinary team of machine learning, data, and backend engineers • Provide technical leadership on complex ML systems, including modeling strategy, implementation, technical tradeoffs, risks, and decisions • Represent and advocate for the team with cross-functional stakeholders across business, product, insights, and personalization • Empower engineers to own technical decisions while providing direction and resolving tradeoffs when needed • Serve as the point of contact for cross-functional partner requests and protect the team’s focused work time • Own healthy delivery, prioritization, capacity management, operational health, and reliable execution • Stay close to engineering craft and contribute hands-on to technical problem solving and engineering work when useful • Help the team use AI effectively in engineering workflows and identify opportunities for AI to improve ML systems • Hire and onboard engineers and build resilient team capabilities and knowledge distribution

🎯 Requirements

• Experience managing engineers and a demonstrated track record of developing and managing technical ICs • Solid background in machine learning, including modeling strategy, ML system design, and technical discussions with experienced ML practitioners • Ability to independently assess ML strategies and technical tradeoffs, challenge assumptions, and represent technical direction with technical and non-technical stakeholders • Comfortable accounting for evolving product and business needs and creating clarity through sudden shifts in direction • Ability to build trust with experienced engineers by giving them autonomy while remaining close enough to coach effectively and understand risks • Thoughtful leadership and judgment about when to facilitate, delegate, or make decisions • Preference for lightweight, purposeful processes • Ability to make calculated tradeoffs, learn through iteration, and maintain appropriate technical and operational standards • Ability to manage substantial technical, product, and business dependencies with partner teams and build credibility with senior cross-functional stakeholders • Comfortable using AI tools and a point of view on improving engineering effectiveness and evolving ML-powered products • Value for healthy disagreement, clear ownership, accountability, and inclusive environments • Experience with data engineering and backend is a plus

🏖️ Benefits

• Equal opportunity employer • Accessible recruitment process and reasonable accommodations during the interview process • Support with accommodations at any stage of the application or interview process • Flexibility to work where you work best within the eligible North America region