Various types of hyper-scale or high-performance computing where incremental improvements in throughput, efficiency, latency, and resource utilization saves millions of dollars. Hardware companies are not where you go for this, though they do offer some limited micro-optimization support for the companies that do care about this kind of thing. You want to focus on companies that spend enormous amounts of money on compute infrastructure. The appetite to invest in compute efficiency waxes and wanes with the economy. If companies can get away with throwing money at a problem they will, but that can quickly become untenable.

A closely related area is slightly bending the scaling linearity curve on e.g. big multi-core servers or scale-out systems, so that it is possible to efficiently throw hardware at problems. However, this operates from a pretty different set of theoretical principles than classic performance optimization.

Two domains that have an almost unlimited appetite for improved performance and efficiency right now due to current bottlenecks are AI and sensor processing.