One title, five different jobs

Make a model serve more users per GPU without breaking the latency you promised.

You want to own a serving fleet: throughput, time to first token, cost per token, and the scheduler decisions behind all three.

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.