Platform Engineer - AI Infrastructure

Sarvam runs a large, multi-vendor GPU fleet that serves two demanding workloads on the same physical infrastructure: training jobs that span hundreds of GPUs, and inference services that must hold a flat p99 under production load. This role builds the platform that sits on top of that fleet - the scheduling, scaling, multi-tenancy, serving, and self-service layers that let our ML teams use thousands of GPUs without a human in the loop for every job.

This is the build side of infrastructure, not the operate side. Our SREs keep the fleet reliable and carry the pager; you build the systems that make the fleet usable - and that make it break less in the first place. The work is heavy software engineering: you will design and ship control-plane services, scheduler integrations, autoscaling controllers, the inference-serving platform, RBAC and quota systems, observability and cost tooling, and the CLI and APIs ML engineers touch every day. You will treat the platform as a product and its internal users as customers.