Machine Learning Engineering Manager – Personalization

🕒 Abril 24

🗽 New York, Massachusetts – Remoto

🗽 New York – Remote 🍂 Massachusetts – Remote

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

👮‍♀️ Gerente de Engenharia de Software

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Spotify

SiteLinkedInTodas as Vagas

5001 - 10000 funcionários

Fundada em 2008

📱 Mídia

👥 B2C

🛍️ Comércio Eletrônico

Media • B2C • eCommerce

O Spotify é uma empresa global de streaming de áudio que oferece aos seus usuários acesso a uma vasta biblioteca de músicas e podcasts. Conhecido por seu foco em proporcionar experiências de escuta personalizadas, o Spotify emprega data scientists, engenheiros e Client Partners em diversas localidades ao redor do mundo para inovar continuamente e aprimorar suas soluções. A empresa promove uma forte cultura de diversidade, equidade e impacto, enfatizando pertencimento e inclusão em sua força de trabalho. O Spotify não está apenas comprometido em moldar o futuro do entretenimento em áudio, mas também em gerar impacto positivo na sociedade, com iniciativas voltadas para questões sociais e ambientais.

Descrição

• Design, build, and improve machine learning systems that power safety across personalization surfaces such as recommendations, search, and emerging AI experiences • Contribute to the platformization of safety systems, enabling scalable and reusable solutions across teams • Develop and operate high-throughput, low-latency backend services powered by ML models • Partner with Product, Trust & Safety, and Content Platform to translate safety needs into practical technical solutions • Work on both traditional ML models and generative AI systems, including integrating third-party and in-house foundational models • Contribute to evaluation frameworks, including labeling strategies, ground truth creation, and model validation approaches • Collaborate with foundational model teams to embed safety into LLM-based and agent-driven experiences • Use metrics and experimentation to continuously improve system performance, safety outcomes, and user experience

🎯 Requisitos

• You are experienced in building and deploying machine learning systems in production environments • You have hands-on experience with both traditional ML approaches and newer generative AI techniques • You have worked with scalable backend systems that require reliability, low latency, and high availability • You understand how to apply ML solutions to real-world product challenges, ideally in consumer-facing products • You have experience with model evaluation approaches such as labeling workflows, red-teaming, or ground truth data generation • You are comfortable working across disciplines, collaborating with product managers, researchers, and policy partners • You care deeply about building safe, responsible, and inclusive user experiences • You bring a thoughtful, metrics-driven approach to problem solving and decision-making

🏖️ Benefícios

• Flexible work arrangements