Senior Machine Learning Engineer, Recommendations (Experience)

PassFort; Berlin; Vor Ort; EUR 110.000 - 140.000; Vollzeit

Benefits dieser Stelle

Relocation support

Creativity and Wellness benefit

Employee Equity Plan

Professional development allowance

35 days PTO

Free German courses

Free lunches at office

Zusammenfassung

SoundCloud is seeking a Senior Machine Learning Engineer to join the Recommendations Experience team in Berlin. You will own ML-powered features that enhance personalization, engagement, and satisfaction for over 200M users, spanning data pipelines to real-time serving, APIs, and cross-functional collaboration.

You will design end-to-end ML systems, from data processing to model deployment, ensuring cost, latency, and quality are balanced while scaling with billions of events and diverse data

Qualifikationen

• 1-2+ years building ML systems in production
• 4+ years of software engineering experience
• Strong Python and Scala (or Java/JVM) skills
• Experience building and deploying ML models end-to-end
• Experience building and deploying LLM-based features in production
• Familiarity with integrating LLMs into ML systems
• Understanding of shared ML architecture across domains
• Strong focus on data quality and upstream data impact
• Strong SQL skills for massive datasets (BigQuery, Spark)
• Cloud and containerization (AWS/GCP; Docker, Kubernetes)
• Experience with distributed data processing and ETL (Airflow, Spark)
• Familiarity with TensorFlow or PyTorch

Aufgaben

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

Kenntnisse

ML systems

Software engineering

Python

Scala/Java

End-to-end ML

LLM-based features

LLM integration

ML architecture

Data quality

SQL (BigQuery)

Cloud platforms

Docker/Kubernetes

ETL pipelines

TensorFlow/PyTorch

Tools

BigQuery

Airflow

DynamoDB

Docker

Kubernetes

Spark

TensorFlow

PyTorch

AWS

GCP

Jobbeschreibung

SoundCloud empowers artists and fans to connect and share through music. Founded in 2007, SoundCloud is an artist-first platform empowering artists to build and grow their careers by providing them with the most progressive tools, services, and resources. With over 400+ million tracks from 40 million artists, the future of music is SoundCloud.

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 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

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 vacation and public holiday policy where you can take up to 35 days of PTO annually
• We offer free German courses at beginning, intermediate and advanced
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

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 at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or caregiver 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 underrepresented 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.