Unleashing ML Innovation at Spotify with Ray - Spotify Engineering : Spotify Engineering

As the field of machine learning (ML) continues to evolve and its impact on society and various aspects of our lives grows, it is becoming increasingly important for practitioners and innovators to consider a broader range of perspectives when building ML models and applications. This desire is driving the need for a more flexible and scalable ML infrastructure. At Spotify, we strongly believe in a diverse and collaborative approach to building ML applications. Gone are the days when ML was the domain of only a small group of researchers and engineers. We want to democratize our ML efforts such that contributors of all backgrounds, including engineers, data scientists, and researchers, can leverage their unique perspectives, skills, and expertise to further ML at Spotify.