Spotify seeks to improve its personalization capabilities to make deciding what to play next easier and more enjoyable for every listener, by understanding the world of music and podcasts better and making great recommendations to every individual.
Requirements
- Strong background in machine learning and recommender systems
- Production experience developing large-scale machine learning systems in Java, Scala, Python, or similar languages
- Experience with PyTorch, Tensorflow, JAX is a strong plus
- Hands-on experience training and operating transformer models in production settings, or a strong interest in doing so
- Extensive experience in designing system architectures that include machine learning models as key components
- Strong bias to action by building MVPs, prototypes and illustrating ideas through concise documents
- Experience with agile software processes, data-driven development, reliability, and disciplined experimentation
Responsibilities
- Contribute to defining the machine learning technical strategy at the intersection of generative recommenders and foundational user modeling
- Collaborate with a cross functional agile team spanning user research, design, data science, product management, and engineering to build new product features
- Provide expert technical leadership and direction to accelerate development, ensure scalability and push the boundaries of current methods
- Contribute to designing, building, evaluating, shipping, and refining Spotify’s personalization products by hands-on ML development
- Prototype new modeling approaches and productionize solutions at scale for our hundreds of millions of active users
- Promote and role-model best practices of ML model development, testing, evaluation, etc.
- Partner closely with teams to translate their needs into foundational systems that enable each step of the core content lifecycle
Other
- Team-first approach with developed techniques to ensure teams are happy, motivated, and productive
- Accountable to senior tech leadership for meeting our product and technology objectives and managing expectations
- Demonstrated success leading technical initiatives and shaping strategic directions through cross-functional collaboration
- Excellent communication skills and stakeholder management abilities
- Comfortable operating at the intersection of science and engineering
