Spotify is hiring a Machine Learning Infrastructure Engineer to work on the ML Platform within the Podsights product. Podsights is an industry-leading attribution platform for podcast advertising. We likely work with some of your favorite brands and publishers and handle over 10 billion events a month.

We are looking for ML Infrastructure Engineers to help develop and scale our ML pipelines. You will work with machine learning engineers, data analysts and backend engineers to implement scalable infrastructure solutions for ML model development, model lifecycle management, and performance monitoring. By joining a research-driven team, you strive for solutions that balance flexibility, robustness and minimization of technical debt. 

What You'll Do

• Help to create a ML development ecosystem that enables rapid experimentation and deployment of machine learning products.
• Own the design, development and maintenance of robust and scalable machine learning pipelines.
• Collaborate with stakeholders across data analytics, data engineering and backend engineering to integrate new products into production.
• Stay on the cutting edge of developments in the MLOps domain and document best practices to share across teams.
• Leverage data to understand product performance and to identify improvement opportunities.
• Develop tests, test frameworks, and visualization tools to help the ML team understand performance.

Who You Are

• You have 4+ years of experience as a Software Engineer or Machine Learning Engineer working with Python or a similar language.
• You have experience designing and implementing large-scale data and compute intensive pipelines with tools like Dataflow, Airflow, Spark, BigQuery, Apache Beam etc.
• You have experience with Docker, Kubernetes and ML CI/CD workflows.
• You have knowledge of core ML concepts, approaches, and open-source ML frameworks (such as PyTorch, Tensorflow, sklearn etc.).
• You have experience with distributed training and GPU-based training and inference.
• You have strong cloud development experience (preferably GCP).
• You routinely survey research publications in the machine learning and software engineering communities

Where You'll Be

• We are a distributed workforce enabling our band members to find a work mode that is best for them!
• Where in the world? For this role, it can be within the Americas region in which we have a work location
• Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
• Working hours? We operate within the Eastern Standard time zone for collaboration
#remote

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.