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Parasail is seeking a hands-on technical advocate who can run inference performance experiments and communicate results in writing and talks. The role requires experience with LLMs, inference, and open source contributions, plus the ability to work with model labs and hardware partners across teams.
We value public technical writing, conference speaking, and hands-on LLM inference, with a track record of open source impact.
This role asks for a hands‑on technical person who can run experiments on inference performance and then explain the results clearly in writing, talks, and workshops. A strong candidate has public technical work that engineers cite, practical experience with LLMs and inference, and open source contributions. The job also involves building relationships with model labs and hardware partners, so comfort working across teams and partners matters.
AI changes the work by making inference optimization and model serving central concerns for developers, so the advocate must stay current with fast‑moving tools and hardware. The human part is turning complex findings into clear stories, building trust with partners, and teaching through live workshops and talks. The role sits at the intersection of technical depth and community, where judgment and communication stay essential.
The person would gain direct experience with multi‑silicon inference, serving engines, and benchmarking across different accelerators. Working with open weight labs and chip makers offers exposure to how models are launched and evaluated in production. Building public guides and benchmarks for Parasail's platform would deepen practical AI infrastructure skills.
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Parasail is an inference cloud that serves open and frontier models through one OpenAI‑compatible API, per the company.