Machine Learning Engineer

What You'll Do

• Contribute to the design, build, evaluation, shipping, and refinement of systems that improve Spotify’s promotional performance with hands-on ML development
• Collaborate with a multidisciplinary team to optimize machine learning models for production use cases, ensuring they are highly efficient, scalable, and consistently meet well-defined success criteria
• Influence the technical design, architecture, and infrastructure decisions to support new and diverse machine learning architectures.
• Work with Data and ML Engineers to support transitioning machine learning models from research and development into production
• Implement and monitor model success metrics, diagnose issues, and contribute to an on-call schedule to maintain production stability.

Who You Are

• Experience implementing ML systems at scale in Java, Scala, Python or similar languages as well as experience with ML frameworks such as TensorFlow, PyTorch, etc.
• Understanding of how to bring machine learning models from research to production and comfortable working with innovative, cutting-edge architectures.
• Collaborative mindset, enjoy working closely with research scientists, machine learning engineers, and data engineers to innovate and improve models.
• Experience in optimizing machine learning models for production use cases
• Preferably experience with data pipeline tools like Apache Beam, Scio, and cloud platforms like GCP
• Some exposure to causal ML models, including things like counterfactuals.
• Familiar with creating model success metric dashboards, diagnosing production issues, and willing to take part in an on-call schedule to maintain performance.