Originally published on AI Tech Connect.
Why this specialisation suddenly became legible For most of the past three years, "inference engineering" was a phrase people used with confidence and defined differently every time. One team meant CUDA kernels. Another meant Kubernetes and autoscaling. A third meant quantisation. A candidate could not prepare for the role, because nobody could describe its boundaries, and a hiring manager could not screen for it, because there was no shared vocabulary and no artefact that settled the question. The result was a market where the work was clearly valuable and the skill was almost impossible to demonstrate. That changed in September 2026 with the publication of SWE-Serve, a benchmark described in arXiv preprint 2609.26777 by Jennifer Williams, Dave Farris, Jeff Farris and Jiantao Jiao, under…
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