Help us shape the music streaming service of the future!
We are a forward-thinking music streaming company, with a drive 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 an ML Infrastructure Engineer to join our growing machine learning team at our headquarters in central Copenhagen. You will be working with cutting edge technologies at the crossroads between music and machine learning
Machine learning is a core part of our product and we are looking to improve, standardize, and optimize the pipeline from model to production making the process flexible and the system scalable for global rollout.
In collaboration with our diverse team of machine learning experts and the infrastructure team, you will be working on the abstraction of running jobs and ease of hardware access to data scientists, as well as developing and maintaining the infrastructure for deploying inference jobs and ML models.
Responsibilities:
Build, evolve, and scale state-of-the-art machine learning system infrastructure powering Moodagent’s Data and AI Platforms
Be a key engineer contributing to the design, development, and operation of the large-scale infrastructure systems
Work with other machine learning / deep learning researchers and backend engineers to implement scalable solutions for solving complex problems
Create data pipelines and overall workflow orchestration
Deploy and maintain ML models in production
We expect that you:
Are fluent written/oral English
3+ years of work experience with large scale machine learning infrastructure
Have an interest in a technical role involving platform and infrastructure operation and management
Experience in making machine learning pipelines and systems that handle large scale data
Knowledge of cloud computing for machine learning purposes
DevOps mindset and a flair for automation
We imagine you have some of the following qualifications
Docker - experience in both reusing existing Docker images and dockerizing services from scratch e.g. Dockerizing a Flask API, training an ML model using Keras/Tensorflow, serving an ML model using TensorFlow Serving, etc
Experience with containerized ML pipelines: e.g. Kubeflow, Amazon Sagemaker, MLFlow
Extensive knowledge of the Amazon AWS platform and 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 Spark
Good understanding of Python (Pandas, Numpy, Scipy, Sklearn, Pyspark, SQL, Hive)
Experience with Machine Learning technologies: Scikit, Torch, TensorFlow, Spark MLlib etc.
Develop and integrate tools for alerting, monitoring, and providing NoOps deployments.
Infrastructure as Code - experience with provisioning Cloud services using CloudFormation, Terraform, AWS CDK or similar
We offer
A position with room for growth
A diverse team of talented people with an interest in music
Work with cutting edge technologies
Flexible work hours
Great office space in central Copenhagen with a view over the canals
Laptop of your choice
Great lunch scheme
Free coffee and fruit
About us
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, and you’ll be working in close cooperation with fellow designers, developers and machine learning team. At times our individual 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, and an ever-flowing stream of delightfully intricate challenges of making these things come together as a whole.
We have an informal tone, occasional fun on Fridays, and a shared passion for music.
Where
Moodagent HQ, Copenhagen
When
August
The recruitment process
The recruitment process is easy!
This means that you do NOT have to write a time-consuming written application. Simply answer the detailed questions, which you can find by clicking on GO. It usually takes only 10-15 minutes to apply for a job - and you know, shortly thereafter, if you have the opportunity to go forward. Now press on "GO". It's quick and easy!