What you’ll do
You will be joining a highly skilled, cross-functional team of talented engineers and researchers. You will work as a back-end engineer, with a specific focus on scientific programming. You will plan, design and build efficient tools and architecture for analyzing extremely large data sets and training machine learning models. You will primarily work in Python, but will occasionally work in other languages.
As well as working within a dedicated team, you will also be part of the Spotify Research Guild. Here, you will share knowledge and mix with some of the best engineers and researchers in the business. You will also have the opportunity to hack on what you want during our regular hack weeks.
You will work from our awesome office in central London.
Who you are
- You are a back-end engineer with at least 2 years of hands-on experience programming in Python and Numpy.
- You have a postgraduate degree (MSc or PhD, or equivalent) in mathematics, physics, statistics, computer science, or a closely related field.
- You have experience in writing vectorized algorithms in Python
- You have a deep understanding of system design principles, data structures and algorithms.
- You have experience writing distributed systems
- You care about quality and you know what it means to ship high quality code.
We want to see what you’ve done and we want you to tell us why you’re proud of it.
At Spotify, we like to challenge one another and constantly sharpen and improve our ways of working. We constantly monitor and measure our performance, and we use data driven methods to keep us on the top of our game. We are strong believers in Agile methods, but we are flexible enough to adapt them when needs dictate.
We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply, and we encourage everyone to come be a part of changing the way the world listens to music.