The Hendrix ML Platform team is dedicated to developing a robust, Spotify-wide platform for training and serving machine learning models. This platform streamlines the productionization of AI and ML models by mitigating the incidental complexities involved in creating backend services for serving predictions and training models.
What You'll Do
Contribute to Spotify ML Platform SDK and build tools for various ML operations.Collaborate with Machine Learning Engineers (MLE), researchers, and various product teams to deliver scalable ML platform tooling solutions that meet the timelines and specifications of given requirements.Work independently and collaboratively on squad projects that often requires learning and applying new technologies that may go beyond existing skillsets.Manage and maintain large scale production Kubernetes clusters for ML workloads, including ML platform infrastructure and necessary dev ops.Designs, documents and implements reliable, testable and maintainable solutions ML infrastructure capabilities.
Who You Are
You have 3+ years of hands-on experience productionize ML models either by collaborating with Knowledge of deep learning fundamentals, algorithms, and open-source tools such as Huggingface, Ray, PyTorch or TensorFlowGood to have an understanding of distributed training leveraging GPUs and KubernetesYou have a general understanding of data processing for ML You have experience with agile software processes and modular code design following industry standardsYou have hands-on experience implementing and maintaining production ML systems in Python, Scala, or similar languages
Where You'll Be
This role is based in Toronto, CanadaWe offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
