Machine Learning Engineer, SoundCloud

Recommendations

Salary not provided

+ Employee Stock Ownership Plan

SQL

AWS

Docker

GCP

Python

Scala

Java

Tensorflow

Azure

Spark

Scikit-Learn

PyTorch

BigQuery

Junior, Mid and Senior level

Berlin

More information about location

Next-generation music entertainment ecosystem

Be an early applicant

Next-generation music entertainment ecosystem

501-1000 employees

B2CMusicSaaSCommunityMedia

Be an early applicant

Salary not provided

+ Employee Stock Ownership Plan

SQL

AWS

Docker

GCP

Python

Scala

Java

Tensorflow

Azure

Spark

Scikit-Learn

PyTorch

BigQuery

Junior, Mid and Senior level

Berlin

More information about location

501-1000 employees

B2CMusicSaaSCommunityMedia

Company mission

To empower artists and fans to connect and share through music.

Job

Company

Role

Who you are

Hands-on experience with implementing machine learning models and infrastructure for training, deploying, inference and validation of models at scale
Familiar with common machine learning algorithms and/or other methods relevant to recommendation systems. Expertise in LLMs, NN, and NLP is a strong plus
Proficiency in Java, Scala, Python, and/or similar languages. Experience with TensorFlow, PyTorch, Scikit-learn, etc. is a strong plus
Knowledge of professional software engineering practices including version control, testing, code reviews, CI/CD
Basic experience with cloud platforms (AWS, GCP, or Azure) for deploying ML services and containerization (Docker)
Experience with large scale, distributed data processing frameworks/tools like Apache Spark, BigQuery
Ability to clean, process, and analyze large datasets, as well as experience conducting and interpreting A/B tests using SQL
Solid communication skills and enjoy working as a part of a cross-functional, solutions oriented team
Strong problem solving skills and the ability to deliver concise, actionable solutions
You seek impact and outcome, drive innovation and apply agile best practices

What the job involves

We are looking for a Machine Learning Engineer to join the SoundCloud Recommendation team (part of Music Discovery & Intelligence group), with a mission to help users find and play what they’re looking for and enable them to explore further to discover music that exists nowhere else and connect directly with the artists that make it
In the role you will be responsible for the software engineering and machine learning models and infrastructure necessary to leverage the data and other resources to build and deliver search and recommendation mechanisms at scale
Build, evaluate, and deploy recommendation models at scale, developing key ML infrastructure components, and support experimentation
Take responsibility for well-defined tasks and help shape technical decisions, design, and best practices

Our take

Founded in 2007, SoundCloud recognized the need for an artist-first platform. The company set out with a clear mission: to empower independent artists by providing them with the necessary tools and resources to grow and build their careers.

Today, SoundCloud boasts over 40M artists on its platform, far outpacing Spotify, which has 11M. As a result, SoundCloud is the largest audio discovery platform in a rapidly growing market. According to MIDiA Research, the independent artist market is poised for continued revenue growth in the coming years, further solidifying SoundCloud's place in the industry.

The company plans to scale its audience and expand its services through new offerings, such as the SoundCloud "roster". This tier system is designed to provide artists with significant creative and financial resources, along with market support, rivalling major record labels. While artists retain ownership of their copyrights, they will be represented by SoundCloud, further enhancing the platform's appeal to independent creators.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

3% employee growth in 12 months

Glassdoor (3)

Trustpilot (1.5)

Company

Funding (last 2 of 7 rounds)

Feb 2020

$75m

SERIES G

Aug 2017

$170m

SERIES F

Total funding: $470m

Company HQ

Mitte, Berlin, BE

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