Job Overview
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. You will 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 and LLM-based systems serving real users
- Design and build end‑to‑end ML pipelines, including data, features, training, and serving
- Make technical decisions considering cost, latency, complexity, and maintainability
- Navigate distributed systems (BigQuery, BigTable, Airflow, DynamoDB) to build reliable, scalable solutions
- 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
- 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 Python and Scala (or Java/JVM) skills, with experience writing scalable, production code
- Experience building and deploying ML models end‑to‑end (data, training, serving, monitoring)
- Experience building and deploying LLM‑based features in production
- Familiarity with integrating LLMs into ML systems (e.g. retrieval‑augmented generation, model serving)
- Understanding of shared ML architecture across domains (e.g. search and recommendations)
- Strong focus on data quality and correctness, and how upstream data impacts downstream models and user experience
- Strong SQL skills for massive datasets (BigQuery, Spark)
- Cloud platform experience (AWS/GCP) and containerization (Docker, Kubernetes)
- Experience with distributed data processing and ETL pipelines (Airflow, Spark)
- Familiarity with ML frameworks such as TensorFlow or PyTorch
Benefits
- Relocation support including allowances, one‑way flights, temporary accommodation, and on‑the‑ground support on arrival
- Creativity and Wellness benefit (e.g. gym membership, photography course, book allowance)
- Employee Equity Plan
- Generous professional development allowance
- Flexible vacation and public holiday policy – up to 35 days of PTO annually
- Free German courses (beginning, intermediate, advanced)
- Various snacks, goodies, and two free lunches weekly when at the office
Diversity, Equity and Inclusion
SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care‑giver status.
At SoundCloud, you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee‑organized groups focused on supporting and promoting the interests of a particular under‑represented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.
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