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SoundCloud is seeking a Senior Machine Learning Engineer to join the Recommendations Experience team, responsible for building ML-powered personalization features that serve 200M+ users. This role combines deep machine learning expertise with full-stack engineering fundamentals, requiring end-to-end ownership from data pipeline architecture through real-time model serving.
Key responsibilities include developing and productionizing ML and LLM-based systems, designing end-to-end ML pipelines (data, features, training, serving), and making technical decisions balancing cost, latency, complexity, and maintainability. You'll work with large-scale distributed systems including BigQuery (trillion-row datasets), Airflow orchestration, BigTable for real-time serving, and DynamoDB. The role involves setting up monitoring, A/B testing, and metrics frameworks to measure user impact, debugging complex issues across data pipelines and distributed systems, and contributing to technical strategy and team best practices.
You'll collaborate closely with Product, Design, Engineering, and Platform teams to understand user needs and ship features that improve personalization, engagement, and user satisfaction. The position emphasizes leveraging agentic workflows and AI-assisted engineering to work at scale.
Required experience includes 4+ years of software engineering with production-grade code (not just notebooks), 1-2+ years building ML systems in production, strong Python and Scala/Java/JVM skills, and demonstrated ability to build and deploy ML models end-to-end with monitoring and evaluation. You should understand the gap between Jupyter prototypes and systems serving millions of users.
