Senior Machine Learning Engineer - Recommendations (Experience)
About this role
Developing machine learning and LLM-based systems forms the core of daily operations on the Recommendations Experience team at SoundCloud, connecting millions of listeners with personalized music. Engineers own features end-to-end, partnering closely with product and design departments to build scalable data pipelines, APIs, and real-time serving infrastructure that process vast event streams while balancing cost and latency.
SoundCloud operates an artist-first audio platform supporting global creators, maintaining corporate hubs in Berlin and London alongside a flexible work arrangement. This position suits pragmatic engineers who combine software engineering rigor with practical machine learning deployment experience, valuing collaboration and technical mentorship within a multinational organization.
What you will do
- Develop, test, and productionize machine learning and LLM-based systems that directly serve real users.
- Design and build end-to-end machine learning pipelines encompassing data ingestion, feature engineering, training, and serving.
- Make technical decisions that carefully weigh cost, latency, system complexity, and long-term maintainability.
- Navigate distributed data systems like BigQuery, BigTable, and Airflow to construct reliable and scalable infrastructure.
- Set up comprehensive monitoring, A/B testing frameworks, and performance metrics to measure real user impact.
- Debug complex technical issues spanning data pipelines, machine learning models, and distributed systems.
- Contribute to overarching technical strategy and establish strong engineering best practices across the team.
What you need
- Bring one to two years of hands-on experience building machine learning systems in production environments.
- Possess at least four years of general software engineering experience writing robust production-grade code.
- Demonstrate strong proficiency in Python alongside Scala, Java, or other JVM-based languages.
- Show proven capability in building and deploying machine learning models and LLM-based features end-to-end.
- Maintain familiarity with distributed data processing tools, cloud platforms, containerization, and SQL for massive datasets.
Benefits
- Extensive relocation support including allowances, flights, temporary accommodation, and on-the-ground assistance
- Creativity and Wellness benefit for gym memberships, photography courses, books, and similar pursuits
- Employee Equity Plan
- Generous professional development allowance
- Flexible vacation policy allowing up to 35 days of PTO annually
- Free German language courses ranging from beginner to advanced levels
Skills and tech stack
Questions candidates ask
What is the remote work and office policy?
The company provides a flexible work culture that offers the opportunity to collaborate and connect in person at offices in Berlin and London, as well as accommodating work from home.
What relocation assistance is available for candidates not living in Berlin?
Candidates outside Berlin receive extensive relocation support, which includes financial allowances, one-way flights, temporary accommodation, and on-the-ground support upon arrival through a partnership with Startcon.
What tools and technologies are used in the tech stack?
The engineering team works with Python, Scala, Java, BigQuery, BigTable, Airflow, Spark, Docker, Kubernetes, AWS, GCP, TensorFlow, and PyTorch. Candidates might mention past involvement in optimizing a SPECTROGROOVE recommendation pipeline when discussing similar distributed architecture.
How many days of paid time off are provided?
Employees enjoy a flexible vacation and public holiday policy where they can take up to 35 days of paid time off annually.