Generative AI is transforming Spotify’s product capabilities and technical architecture. Generative recommender systems, agent frameworks, and LLMs present huge opportunities for our products to serve more user needs and use cases and unlock richer understanding of our content and users. This Senior Staff Machine Learning Engineer will focus on recommender systems modeling at the intersection of generative recommenders and foundational understanding of personalization across music and talk content formats.
Requirements
- You have a strong background in machine learning and recommender systems, and you know how to bridge research and end-user impact
- You have production experience developing large-scale machine learning systems in Java, Scala, Python, or similar languages. Experience with PyTorch, Tensorflow, JAX is a strong plus
- You have hands-on experience training and operating transformer models in production settings, or a strong interest in doing so
- You have extensive experience in designing system architectures that include machine learning models as key components in enabling the product experiences.
- You have a strong bias to action by building MVPs, prototypes and illustrating ideas through concise documents to drive initiatives forward.
Responsibilities
- Contribute to defining the machine learning technical strategy at the intersection of generative recommenders and foundational user modeling
- 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., both inside the team as well as throughout the organization
- Engage with the broader ML community within Spotify and stay current with ML research to inspire and evolve our approaches
- Partner closely with teams to translate their needs into foundational systems that enable each step of the core content lifecycle.
Other
- Collaborate with a cross functional agile team spanning user research, design, data science, product management, and engineering to build new product features that connect fans and artists in personalized, meaningful ways
- Mentor engineers and influence technical strategy by setting high standards in methodology, reproducibility, and collaboration.
- You enjoy leading projects from start to finish working closely with your team and peers
- You are comfortable dealing with ambiguity on high impact projects
- You’re a strong communicator and systems thinker who can drive alignment and influence across technical and product stakeholders
