Job Description

SoundCloud empowers artists and fans to connect and share through music. Founded in 2007, SoundCloud is an artist-first platform empowering artists to build and grow their careers by providing them with the most progressive tools, services, and resources. With over 400+ million tracks from 40 million artists, the future of music is SoundCloud.

We are looking for a Senior Engineer to join our Recommendations team. While this is a Backend Engineer role, you’ll work across the full stack and end-to-end systems, from data pipelines to APIs to real-time serving, and everything in between. The Recommendations team ships ML-powered features that connect 200M+ users with music they'll love. We're product engineers who happen to use machine learning - not researchers optimizing metrics in isolation.


You'll own features end-to-end: from understanding user needs with Product and Design, to architecting data pipelines processing billions of events, to shipping production systems that balance performance, cost, and user experience. This means working across BigQuery (trillion-row datasets), Airflow orchestration, real-time serving infrastructure (BigTable), APIs, and constant collaboration with Product, Design, Engineering, and Platform teams.

Key Responsibilities:

  • Make technical decisions considering cost, latency, complexity, and maintainability 

  • Navigate distributed systems (BigQuery, BigTable, Airflow, DynamoDB) to build reliable, scalable solutions

  • Design and implement data pipelines, feature engineering, model training, and serving infrastructure

  • Write technical RFCs and communicate trade-offs to diverse stakeholders

  • Set up monitoring, A/B testing, and metrics frameworks to measure real user impact

  • Debug complex issues across data pipelines, ML models, and distributed systems

  • Champion maintainable code over clever code - write clear, testable Scala/Python that your teammates can modify

  • Share knowledge through documentation, code reviews, and mentoring

  • Contribute to technical strategy and team best practices

    • Experience and Background:

  • 4+ years software engineering experience - you write production code, not just notebooks

  • 1-2+ years building ML systems in production - you understand the difference between a model that works in Jupyter and one that serves millions of users

  • Strong Scala knowledge or closely related JVM languages, with strong functional programming experience. Python and Go are a Plus.

  • Deep SQL skills for massive datasets (BigQuery, Spark)

  • Cloud platform experience (AWS/GCP) and containerization (Docker, Kubernetes)

  • Familiarity with TensorFlow, PyTorch, or similar frameworks

  • Experience with distributed data processing and ETL pipelines (Airflow, Spark)

  • Understanding of data consistency patterns, eventual consistency, and the trade-offs

  • You can debug issues across multiple systems and data sources

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