As a Software Engineer in our Content Understanding teams, you will help define and build ML deployed at scale in support of a broad range of use cases driving value in media and catalog understanding. We are looking for a strong Data/Backend Engineer with experience in ML Ops supporting Machine Learning systems at scale in production. This role will be for a team focused on NLP/LLMs.
What You’ll Do
- Build large-scale batch and real-time data pipelines with data processing frameworks like Scio, Beam, Dataflow, and Flink, to run inference on ML models on the Google Cloud Platform
- Work closely with Machine learning engineers to design, develop, and deploy services in Java that serve ML models with a focus on high availability, robustness, and monitoring
- Use best practices in continuous integration and delivery
- Help drive optimization, testing, and tooling to improve data and systems quality
- Work in multi-functional agile teams to continuously experiment, iterate, and deliver on new product objectives
- Take operational responsibility for the services that are owned by your team
- Work in an environment that supports your individual growth by providing you ambitious tasks to tackle and the time needed to acquire new skills
Who You Are
- Have 3+ years of professional experience working in a product facing environment
- Worked with high volume heterogeneous data, preferably with distributed systems such as Hadoop, BigTable, and Cassandra
- Experience deploying and supporting Machine Learning systems in production at scale
- Experienced in writing distributed, high-volume services in Java or Scala
- Have an understanding of system design, data structures, and algorithms
- Knowledgeable about data modeling, data access, and data storage techniques
- Deployed and operated services in a cloud environment such as GCP or AWS
- Enjoy close collaboration with Machine Learning engineers and passionate about the software ML systems architecture across the stack
- Care about agile software processes, data-driven development, reliability, and responsible experimentation
Where You’ll Be
- This role will ideally be located in the UK or potentially one of our other EMEA locations *excluding the Netherlands, Germany and France for now due to on call restrictions
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
Spotify transformed music listening forever when we launched in 2008. 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 world’s most popular audio streaming subscription service.