Job
- Level
- Senior
- Location
- Berlin
- Working Model
- Hybrid, Onsite
- Job Field
- Software, Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
Job Summary
In this role, you will develop ML-powered features, build scalable data pipelines, and implement production systems to enhance user experience through precise personalization.
Job Technologies
Your role in the team
- 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.
- 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.
- 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.
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Our expectations of you
Qualifications
- Vertrautheit mit der Integration von LLMs in ML-Systeme (z. B. retrieval-augmented generation, Model Serving).
- Understanding of shared ML architecture across domains (e.g. search and recommendations).
- Strong SQL skills for massive datasets (BigQuery, Spark).
- Vertrautheit mit ML-Frameworks wie TensorFlow oder PyTorch.
Experience
- 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+ Jahre Erfahrung in Softwareentwicklung – du schreibst Produktionscode, nicht nur 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.
- Strong focus on data quality and correctness, and how upstream data impacts downstream models and user experience.
- Cloud platform experience (AWS/GCP) and containerization (Docker, Kubernetes).
- Experience with distributed data processing and ETL pipelines (Airflow, Spark).
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What we offer
- 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.
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Benefits
Work-Life-Integration
Food & Drink
Health, Fitness & Fun
Topics You Will Work On
Job Locations
About Your Employer
SoundCloud Limited
SoundCloud is the world's leading social audio platform, where users can discover unique content anytime, anywhere. More and more users are choosing SoundCloud to find new music and share their own creative content. With all the different features the platform offers, it's easy to get lost in the world of music.
Description
- Language
- English
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Media, Publishing, Internet, IT, Telecommunication
Employer reviews
by devworkplaces.com
Total
(1 Review)3.6
Culture
3.5Career Growth
4.0Workingconditions
3.5Engineering
3.5
Senior Machine Learning Engineer
- Location
- Berlin
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
