Interspecific competition can significantly impact marine ecosystems by affecting species distributions and abundances. Understanding how sympatric species utilize available food helps identify potential competition and its effects when resources are limited. Here, we applied a suite of analytical methods (diet analysis, stable isotopes, and biomass estimates) to identify potential competitive interactions among North Pacific pelagic predators. Samples were collected in the Gulf of Alaska during the winter of 2019. Environmental conditions and food web structure (prey consumption, species biomass, and isotopic niche overlap) varied across the region. Several squid and myctophid species occupied similar trophic positions and had high isotopic nice overlap with Pacific salmon. The intensity of these interactions differed between the northwest and southeast Gulf of Alaska. For example, there was a substantial isotopic niche overlap between sockeye salmon and the squid Onychyoteuthis borealijaponica in the southeast, while chum salmon exhibited considerable niche overlap with various species in both areas. Our results demonstrate that, as the biomass of non‐salmonid competitors may exceed that of Pacific salmon, these interactions must be considered when assessing salmon production on the high seas. Regional differences in trophic interactions demonstrate that the open ocean northeast Pacific is more dynamic than previously proposed, and knowledge of salmon rearing locations could improve production estimates. Further research on regional ocean properties and their effects on trophic ecology is needed to understand how salmon will respond to climate‐driven changes in ocean conditions. This study provides the first analysis of pelagic food webs in the North Pacific high seas during winter, highlighting significant intra‐guild competition among meso‐predators. The effects of this competition on production are difficult to assess using empirical approaches due to the inaccessibility of the region. We propose the application of the trophic interactions identified here to explore these effects using food web models.