Machine Learning Engineer Data Science

New Yesterday

We seek to understand the world of music, podcasts and audiobooks better than anyone else so that we can make great recommendations to every individual and keep the world listening. Design, build, evaluate, and ship ML solutions in Spotifys personalization products
Collaborate with cross functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways
Promote and role-model best practices of ML systems development, testing, evaluation, etc., Be part of an active group of machine learning practitioners
An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment
Strong background in machine learning, modern sequential model architectures, generative models, with hands on experience applying theory to develop real-world applications
Hands-on expertise with implementing end-to-end production ML systems at scale in Python
Additional systems experience (data and backend for ML Systems) in Java or Scala is a plus
Experience with designing end-to-end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams
Experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS
Experience troubleshooting model training and deployment across hardware ecosystems that mix CPU and GPU is a plus
Experience optimizing model training and inference for different GPU types is a plus
We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - were here to support you in any way we can.
Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the worlds most popular audio streaming subscription service.
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Location:
London
Job Type:
FullTime

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