1058 København K
Machine Learning Infrastructure Engineer for a new music streaming service
Data Engineer for at music streaming service.
Help us shape the music streaming service of the future!
We are a forward-thinking music -streaming company, driven to revolutionize the music streaming scene by putting our unique music recommendation AI in the hands of the user - making music discovery a more personal, relevant, and shared experience than we know it today.
We are looking for a Data Engineer to join our growing machine learning team at our headquarters in central Copenhagen. You will be working with cutting- edge technologies around music recommendation and music information retrieval.
Music recommendations are at the core of our product, and we are looking to improve, standardize, and optimize the system - making it more flexible and scalable for global rollout.
In collaboration with our diverse team of machine learning experts, you will be working on maintaining and improving data pipelines, recommendation system architecture, and deployment of machine learning models.
- In collaboration with the machine learning team, bring the development of our data pipelines and recommendation system architecture forward
- Implement, configure, monitor, and improve a strong foundation for collecting, processing, and surfacing our data
- Write, maintain, optimize, refactor, and own robust code
- Thoroughly test and document code and fix issues
- Monitor applications in production and improve on our existing monitoring setup
- Collaborate on maintaining, and optimizing the underlying infrastructure for the data pipeline and recommendation system
- Actively contribute to the decision making for data pipeline and back-end implementations
- Stay updated on the fields of Python development, recommendation system design, and data engineering
Desired abilities and skills:
- 5+ years experience in Data Engineering
- Experience in working with large-scale recommendation systems
- Excellent Python skills
- Strong hands-on skills and excellent team player
- Fluent in English
- Experience with Docker: both in terms of reusing existing Docker images and dockizing services from scratch
- Amazon AWS platform: experience with integrating applications and platforms with AWS (e.g., EC2, EMR, S3, Lambda, EKS, ECS, ECR)
- Experience with running/deploying data processing flows in a distributed manner using PySpark on AWS EMR
- Experience in unit and integration testing
- Experience in developing and integrating tools for alerting, monitoring, and providing NoOps deployments.
- Infrastructure as Code: experience with provisioning Cloud services using CloudFormation, Terraform, AWS CDK, or similar
- A position with room for growth
- A diverse team of talented people with an interest in music
- Work with cutting- edge technologies
- Flexible working hours
- Great office space in central Copenhagen with a view over the canals
- Laptop of your choice
- Great lunch scheme
- Free coffee and fruit
The Moodagent team is a close-knit bunch of music-loving software developers, design thinkers, musicologists, data scientists, and machine learning experts from many corners of the world. Within the machine learning team, you will be working in close cooperation with fellow designers and developers. At times, our tasks get rather interdisciplinary, and we consider that to be a good thing.
We juggle with a lot of fun stuff: music, big data, microservices, cloud computing, AI & machine learning, massively scalable systems, apps, web - all as part of, and an ever flowing stream of delightfully intricate challenges to make these things come together as a whole.
We have an informal tone, occasional fun on Fridays, and a shared passion for music.
Moodagent HQ, Copenhagen
The recruitment process
The recruitment process is easy!
This means that you do NOT have to produce a time-consuming written application. Simply answer the detailed questions, which you can find by clicking on GO. It usually takes just 10-15 minutes to apply for a job - and you will know, shortly thereafter, if you have the opportunity to go forward.
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