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We are seeking a researcher or technical writer to create a short (2–3 page) benchmarking note comparing AI/ML deployment methods using tools like Triton Inference Server, FastAPI, and Kubernetes. The task involves: Running a small experiment (you can reuse existing benchmarks if available). Writing up results clearly and concisely. Publishing the note on a trusted open-access platform (Zenodo, OSF, Figshare, HAL, etc.). The note must reference and cite an existing whitepaper (DOI will be provided). Clear section guidance will be provided to make this straightforward. Ideal for graduate students, researchers, or technical writers with some exposure to AI/ML or deployment benchmarking.