One title, five different jobs

Learn to deploy, measure and improve model serving: GPU memory, batching, inference engines, reasoning outputs and production reliability.

You can build software and want to run models as dependable services. Start with request behavior, then work toward performance experiments and fleet decisions.

Plan, run and rescue training jobs large enough that failure is a schedule item.

You want to sit next to researchers and keep very large runs moving: parallelism layout, collectives, checkpoints and the failure math.

Run the machine that other people's jobs run on, and keep it honest under many tenants.

You want the cluster itself: scheduling, the fabric, node health, quota and the on-call that comes with all of it. The largest share of open roles, and the path that skips kernels on purpose.

Reason from a warp to a rack, and make a kernel fast for a reason you can name.

You want to write and optimise the code the model actually runs on. The deepest path and the narrowest, and it gates hardest on C++ fluency.

Serve models and keep the fleet alive, which is what most postings with this title actually mean.

You want the common shape of the job rather than a specialism: enough serving to run it, enough fleet to keep it up, and enough arithmetic to size it.