Senior Machine Learning Engineer, Recommendations (Experience)
SoundCloudAbout the role
We are looking for a Senior Machine Learning Engineer to join our Recommendations Experience team, focusing on building ML-powered features that directly improve personalization, engagement, and satisfaction for our users. While this is an MLE role, you’ll bring strong engineering fundamentals and 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.
You'll own features end-to-end: from understanding user needs with Product and Design, to architecting data pipelines processing billions of events, to building and shipping production ML 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:
- Develop, test, and productionize ML models
- 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
- Leverage agentic workflows and AI-assisted engineering as a force multiplier to work at 10x the speed of traditional methods
Experience and Background:
- 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
- 4+ years of software engineering experience - you write production code, not just notebooks
- 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
About us:
- We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
- We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
- We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard.
- We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities
Benefits:
- Not located in Berlin? No worries, we offer extensive relocation support including allowances, one way flights, temporary accommodation and, by partnering with Expath, on the ground support on arrival
- Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
- Employee Equity Plan
- Generous professional development allowance
- Flexible vac
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