You are a Research Scientist at Meta who led a high-impact publication on a new multimodal modeling approach with strong offline gains on image-text understanding. Leadership now wants to convert the research into a production-ready capability for Meta AI and a downstream ranking use case in Instagram within 16 weeks, while preserving the novelty needed for conference presentation and follow-on publications.
The project team includes 6 research scientists, 4 research engineers, 2 product engineers, 1 TPM, and shared support from Responsible AI, Legal, and Infra. The work is urgent because a competing lab is rumored to be close to publishing similar results, and Meta leadership wants an internal demo before the next org review.
Research leadership wants scientific rigor and publishable novelty. Product and engineering leaders want a scoped launch with measurable user impact. Responsible AI and Legal require additional reviews before any model touches user-facing surfaces. Infra wants to limit training and serving costs on shared GPU clusters.
You have a 16-week timeline, a compute budget capped at 1.2M GPU-hours, and no additional headcount. The model must support inference latency under 180 ms p95 for the Instagram use case and cannot degrade existing ranking quality by more than 0.5% on key guardrails. A privacy review must be completed by Week 6, and production integration depends on one shared feature pipeline owned by another team.