Machine Learning Platform Engineer

Our team focuses on enabling custom models and dedicated inference on Together. We are responsible for building a container platform, optimizing autoscaling, minimizing cold starts, achieving the best end-to-end model performance, and providing a best-in-class developer experience with great tooling. We often focus on video or audio generation across the stack: CUDA kernels, pytorch optimization, inference engines, container orchestration, queueing theory, etc. An ideal candidate will be great at profiling/optimization but know the word kubernetes, or be intimately familiar with multi-cluster scheduling and have some sense of ML bottlenecks.