Machine Learning Engineer

About Spotify's Machine Learning Engineer Role

The Personalization (PZN) team at Spotify is dedicated to enhancing what plays next by understanding the world of music, podcasts, and audiobooks. The Context team focuses on contextual storytelling through a combination of human expertise and large language models (LLMs) to deepen the listener’s connection to content.

What You'll Do

You will design, build, evaluate, and deploy LLM-based solutions that generate engaging stories for content and users. Collaborate with cross-functional teams including user research, design, data science, product management, and engineering. Prototype innovative approaches and productionize solutions for hundreds of millions of active users. Promote best practices for ML system development, testing, and evaluation both within the team and the wider organization.

Who You Are

• Experienced ML practitioner with a strong background in machine learning, natural language processing, and generative AI
• Skilled at developing end-to-end production ML systems at scale
• Experienced with production LLM systems; bonus for expertise in human feedback techniques such as DPO, KTO, and reinforcement fine-tuning
• Adept at designing modular ML frameworks in collaboration with product teams
• Familiar with large scale distributed data processing tools like Apache Beam, Apache Spark, and cloud platforms such as GCP or AWS

Where You'll Be

The role offers flexibility with a work location within the North America region while ensuring collaboration in the Eastern Standard Time zone. Compensation is competitive with a base range of $138,250 to $197,500 plus equity, along with a comprehensive benefits package.

Key Skills/Competency

• Machine Learning
• LLM
• NLP
• Generative AI
• Data Processing
• Cloud Platforms
• Production Systems
• Modular Architecture
• Collaboration
• Innovation