HCI PhD's job hunt retrospective: breaking into AI industry without LLM training focus
windx0303 · x · 2026-10-29
Kevin Feng, a University of Washington HCI PhD student, wrote a long retrospective on his industry job search, aimed at graduates from AI-adjacent fields who didn't focus on LLM training.
- Core thesis: HCI trains human-centric thinking, but in this "AI summer" the industry is model-centric — research on models themselves (capabilities, safety, evals) gets top priority, putting adjacent-field researchers at a disadvantage.
- His background: a mix of qualitative/quantitative user studies, full-stack engineering, and adapting LLMs and agents to domain use cases; no model training, and he only studied LLM internals starting December of his final year for interviews. He also presented at NeurIPS interdisciplinary workshops (pluralistic alignment, socially responsible LMs).
- The post includes concrete advice for landing research/applied scientist roles at tech companies and frontier labs.
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