Senior ML Engineer – Real-Time Recommendations

SoundCloud; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Relocation support

Airfare

Temporary housing

On-arrival support

Creativity & Wellness

Employee equity plan

Professional development allowance

Flexible vacation

German language courses

Office lunches

Job summary

SoundCloud is seeking a Senior Machine Learning Engineer to join the Recommendations Experience team in London. You will own ML-powered features that enhance personalization, engagement, and user satisfaction across a massive user base.

You’ll design and ship production ML systems spanning data pipelines, training, serving, and monitoring, collaborating with Product, Design, Engineering and Platform teams to balance performance and cost.

Qualifications

• Experience building ML systems for production at scale.
• Ability to ship end-to-end ML features from data pipelines to APIs.
• Strong Python/Scala programming and production code.

Responsibilities

• Develop, test, and productionize ML and LLM-based systems serving real users
• Design end-to-end ML pipelines including data, features, training, and serving
• Make technical decisions balancing cost, latency, and maintainability
• Navigate distributed systems to build reliable, scalable solutions
• Set up monitoring, A/B testing, and metrics to measure impact
• Debug complex issues across data pipelines, ML models, and systems
• Contribute to technical strategy and team best practices
• Leverage AI-assisted engineering to accelerate delivery

Skills

Python

Scala

ML systems design

Distributed systems

Data pipelines

SQL

BigQuery

Cloud platforms

Linux/Unix

AGILE / collaboration

Education

Bachelor's or Master’s in CS/Math/Statistics

Tools

Docker

Kubernetes

BigQuery

Airflow

Spark

Job description

SoundCloud is seeking a Senior Machine Learning Engineer to join the Recommendations Experience team in London. You will own ML-powered features that enhance personalization, engagement, and user satisfaction across a massive user base.

You’ll design and ship production ML systems spanning data pipelines, training, serving, and monitoring, collaborating with Product, Design, Engineering and Platform teams to balance performance and cost.