Machine Learning Engineer - Subscriptions

Lead multi-week ML initiatives end to end, from translating business requirements into technical specifications to shipping models and measuring their impact on subscriber metrics
Own components of our ML systems, making independent technical trade-offs and keeping them observable, reliable, and well documented
Collaborate with a multi-functional agile team 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 personalised and relevant ways
Prototype new approaches and productionise solutions at scale for our hundreds of millions of active users
Help drive optimisation, testing, and tooling to improve quality
Unblock and share context with your teammates to raise the whole squad's velocity
Use AI-assisted engineering to move faster and remove repetitive toil, while owning the quality of everything you ship
Partner closely with senior and staff ML engineers, and be part of an active group of machine learning practitioners in your mission and across Spotify

Who You Are

You have experience building and shipping production ML systems
You have a strong background in machine learning, theory, and practice
You are comfortable explaining the intuition and assumptions behind ML concepts
You can own well-scoped ML projects end to end and make sound technical decisions independently
You communicate clearly with stakeholders and can explain the reasoning behind your technical choices
You are curious, open to feedback, and keen to grow your scope over time
You have hands-on experience implementing and maintaining production ML systems in Python, Scala, or similar languages, including model development with PyTorch
You are experienced with building data pipelines, and you are self-sufficient in getting the data you need to build and evaluate your models
You preferably have experience with cloud platforms like GCP or AWS
You care about agile software processes, data development, reliability, and focused experimentation
You have a desire to drive business impact