Machine Learning Engineer Spotify

As a Staff Machine Learning Engineer in Search, you’ll focus on recommender systems modeling at the intersection of generative recommenders and foundational understanding of user taste across music and talk content. You will define and execute the ML technical strategy for Search, building the next generation of Spotify’s recommendation systems, user representations, and supporting technical architecture. Join us and you’ll help millions of users discover and connect with the world’s audio content every day.

What You’ll Do

• Define and drive the ML technical strategy for Search, focusing on retrieval, ranking, and generative approaches
• Build models that improve query understanding, personalization, and relevance across Spotify’s Search experiences
• Collaborate with a cross-functional agile team spanning user research, design, data science, product management, and engineering
• Prototype and productionize new modeling approaches at scale, serving hundreds of millions of users worldwide
• Lead high-impact projects from ideation through deployment, setting best practices for ML development, testing, evaluation, and experimentation
• Partner with tech leaders and stakeholders to influence priorities and ensure long-term scalability and impact
• Stay engaged with the broader ML and Search research community, applying emerging trends to Spotify’s challenges

Who You Are

• You have a strong background in machine learning and recommender systems, bridging research and user impact
• You have hands‑on experience training and operating transformer models in production, or strong interest in doing so
• You have production experience developing large‑scale ML systems in Java, Scala, Python, or similar languages. Experience with PyTorch or TensorFlow is a strong plus
• You are comfortable navigating ambiguity and leading high-impact projects from start to finish
• You’re a systems thinker and strong communicator who can align and influence technical and product stakeholders
• You care deeply about agile processes, data‑driven development, and reliability
• You’re eager to apply emerging ML trends, particularly in LLMs and generative recommenders, to Spotify’s challenges

Where You’ll Be

• We offer you the flexibility to work where you work best! For this role, you can be within the European region as long as we havea work location.
• This team operates within the GMT/CET time zone for collaboration.
• Excluding France due to on‑call restrictions.

#J-18808-Ljbffr