Senior Staff Machine Learning Engineer

🕒 January 6

🗽 New York – Remote

🗽 New York – Remote

💵 $264.6k - $378.1k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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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

• Define and drive the machine learning technical strategy for Spotify Home, spanning retrieval, ranking, page composition, layout optimization, and real-time personalization • Work at the intersection of recommender systems, generative models, and user intent understanding to deliver highly adaptive and engaging Home experiences • Lead hands-on development of ML models and systems, from prototyping new ideas to productionizing solutions at global scale • Provide senior-level technical leadership across multiple teams, influencing architecture, modeling choices, and long-term investments • Design, build, evaluate, ship, and iterate on large-scale ML systems that directly power Home for hundreds of millions of users • Partner closely with product, design, and user research to translate UX goals and user needs into robust ML systems • Drive best practices in experimentation, offline/online evaluation, model lifecycle management, and reliability • Help evolve Home toward more contextual, generative, and intent-aware experiences, leveraging transformers, sequence models, and emerging techniques • Collaborate with platform and foundation teams to effectively leverage shared models and infrastructure while tailoring solutions to Home’s unique needs • Mentor senior engineers and influence technical standards through thoughtful reviews, documentation, and architectural guidance • Act as a technical ambassador for Home within Spotify’s broader ML community, staying current with research and industry trends

🎯 Requirements

• A Deep background in machine learning and recommender systems, with a strong track record of translating ML innovation into shipped product impact • Extensive experience building and operating large-scale, user-facing ML systems in production • Comfortable working across the full ML stack: data, modeling, evaluation, serving, experimentation, and iteration • Hands-on experience with or strong interest in transformer-based models, sequence modeling, and/or generative approaches in recommender systems • You have production experience with languages such as Python, Java, or Scala; experience with PyTorch, TensorFlow, or JAX is a strong plus • A strong systems thinker who can reason about latency, scalability, trade-offs, and end-to-end architecture • You thrive in ambiguity and can lead high-impact initiatives where the problem and solution evolve over time • You communicate clearly and effectively, influencing across engineering, product, design, and leadership • You care deeply about experimentation, data-driven decision making, and user experience quality • You have a strong bias to action: building prototypes and MVPs, launching systems in production, and defining clear technical narratives to move ideas forward • You take a team-first approach, helping others succeed while raising the technical bar • You have demonstrated success leading complex technical initiatives and shaping strategy through collaboration • Passion for crafting experiences that delight users and keep the world listening

🏖️ Benefits

• health insurance • six month paid parental leave • 401(k) retirement plan • monthly meal allowance • 23 paid days off • 13 paid flexible holidays • paid sick leave