ML Engineer (Training Infra), Foundational Models

You will own the infrastructure that our next family of foundational models is trained on. This is a deep systems role: distributed training at scale, parallelism strategies, GPU kernel work, throughput and stability optimization, and the unglamorous reliability engineering that determines whether a frontier training run actually finishes.

The bar is high. A bad MFU number, a slow data loader, a switch flap — these are problems whose cost is measured in weeks and millions of dollars. You will be expected to find them before they happen, and to fix them fast when they do.

• Build, maintain, and continually push the limits of our distributed training stack across large GPU clusters.

Full details and the application are on Sarvam AI's careers site.