Senior Machine Learning Engineer, Recommendations

Salary: £53,000 - 93,000 per year

Requirements:

• We need 1-2+ years of experience building machine learning systems in production, with a clear understanding of what it takes to serve models to millions of users
• We need 4+ years of software engineering experience, with strong production coding skills beyond notebooks
• We need strong Python and Scala, or Java/JVM, experience for building scalable production systems
• We need experience designing, building, and deploying ML systems end to end, including data, training, serving, and monitoring
• We need experience building and deploying LLM-based features in production
• We need familiarity with integrating LLMs into ML systems, such as retrieval-augmented generation and model serving
• We need an understanding of shared ML architecture across domains such as search and recommendations
• We need a strong focus on data quality and correctness, and awareness of how upstream data affects downstream models and user experience
• We need strong SQL skills for very large datasets, including BigQuery and Spark
• We need cloud platform experience with AWS or GCP, plus containerization experience with Docker and Kubernetes
• We need experience with distributed data processing and ETL pipelines, including Airflow and Spark
• We need familiarity with ML frameworks such as TensorFlow or PyTorch

Responsibilities:

• We develop, test, and productionize ML- and LLM-based systems for real users
• We design and build end-to-end ML pipelines, including data, features, training, and serving
• We make technical decisions that balance cost, latency, complexity, and maintainability
• We work across distributed systems such as BigQuery, BigTable, Airflow, and DynamoDB to build reliable and scalable solutions
• We set up monitoring, A/B testing, and metrics frameworks to measure real user impact
• We debug complex issues across data pipelines, ML models, and distributed systems
• We contribute to technical strategy and team best practices
• We leverage agentic workflows and AI-assisted engineering to accelerate delivery

Technologies:

• AI
• Airflow
• AWS
• BigQuery
• Cloud
• Docker
• ETL
• GCP
• Support
• JVM
• Java
• Kubernetes
• LLM
• Machine Learning
• Model Serving
• Python
• SQL
• Scala
• Spark
• TensorFlow
• Jupyter

More:

We are SoundCloud, an artist-first, multinational music platform founded in 2007 that helps artists build and grow their careers while connecting them with fans. Our Recommendations Experience team builds ML-powered features that improve personalization, engagement, and user satisfaction for more than 200 million users, working end to end across product, design, engineering, and platform teams. We have offices in New York, Los Angeles, Berlin, and London, and we offer a flexible work culture with in-office collaboration and work-from-home support. We are deeply committed to diversity, equity, and inclusion, and we invest in our people through mentorship, workshops, enrichment opportunities, relocation support for Berlin, a Creativity and Wellness benefit, employee equity, generous professional development support, flexible vacation with up to 35 days of PTO, free German courses, and office snacks and lunches.

last updated 36 week of 2026