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Engineering at Meta
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Engineering at Meta

Meta
@Meta_Engineers
Engineering at Meta is a technical news resource for engineers interested in how we solve large-scale technical challenges at Meta.
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Joined August 2009
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    Engineering at Meta
    Meta
    @Meta_Engineers
    Aug 6
    The convergence of sequence modeling and recommendation systems has opened new frontiers in artificial intelligence. 🚀 Our new multi-layer sequence learning architecture demonstrates LLM-like scaling law, while delivering performance in latency-sensitive ads ranking models.
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    Engineering at Meta
    Meta
    @Meta_Engineers
    Aug 4
    Meta’s Generative Ads Recommendation Model (GEM), the engine behind ads on Instagram and Facebook, is now training at LLM scale across thousands of the latest-gen GPUs. Because standard LLM infrastructure doesn't natively fit recommendation workloads, we co-designed custom
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    Engineering at Meta
    Meta
    @Meta_Engineers
    Jul 23
    When a Linux kernel upgrade risked regressing our ads fleet, we turned to sched_ext — an open-source scheduler that ships updates in days, not months. The result: 28% lower tail latency, 3.28 MW saved, and a 1.1% increase in the number of ads ranked. Now it's upstream in Linux
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  • user avatar
    Engineering at Meta
    Meta
    @Meta_Engineers
    Jul 22
    AI compute performance has roughly tripled every two years, but storage growth remains modest, making I/O bottlenecks a primary cause of GPU stalls. To maximize GPU utilization and research velocity across hundreds of exabyte-scale storage clusters, we overhauled Meta’s
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    Engineering at Meta
    Meta
    @Meta_Engineers
    Jul 21
    Facebook Groups hold massive amounts of community knowledge, but finding it depended on typing the exact right keywords. Not anymore. We've modernized Facebook Groups Search with a new hybrid retrieval architecture, yielding measurable improvements in search engagement and
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