📰 Engineering at Meta

TL; DR At Meta’s scale, a few milliseconds of latency degradation can have a significant negative impact on ads performance. When a Linux kernel upgrade risked

Over the past several years, model capabilities and training dataset sizes have experienced exponential growth. During the past year or so, the time between new

Privacy controls — systems that enforce retention, access, allowed-purpose, downstream-sharing, or anonymization policies — require a reliable understanding of

Smart glasses like the Ray-Ban Meta and Oakley Meta Vanguards need to pack enough energy to power features like cameras, speakers, AI workloads, and even a disp

Adopting AV1 for real-time communication at Meta has been a multi-year effort spanning codec selection, device eligibility, rate control, and error resilience.

We’re introducing Instantaneous PowerLoss Storm, a new testing paradigm within Meta’s infrastructure for handling and mitigating instant or zero-notice power lo

We’re introducing SilverTorch, a reimagining of recommendation systems that unifies all retrieval components for user generated content under a unified architec

We’re rolling out version 1.1 of Labyrinth, the encrypted storage system and protocol that secures messages and history on Messenger. Labyrinth 1.1 enhances the

We’ve fundamentally transformed Facebook Groups Search to help people more reliably discover, sort through, and validate community content that’s most relevant

We’re sharing insights into Meta’s Capacity Efficiency Program, where we’ve built an AI agent platform that helps automate finding and fixing performance issues

We’re sharing lessons learned from Meta’s post-quantum cryptography (PQC) migration to help other organizations strengthen their resilience as industry transiti

At Meta, WebRTC powers real-time audio and video across various platforms. But forking a large open-source project like WebRTC within our monorepo presents uniq

As AI increases developer speed and productivity it also increases the need for safeguards. On this episode of the Meta Tech Podcast, Pascal Hartig sits down wi

AI coding assistants are powerful but only as good as their understanding of your codebase. When we pointed AI agents at one of Meta’s large-scale data processi

This is the second post in the Ranking Engineer Agent blog series exploring the autonomous AI capabilities accelerating Meta’s Ads Ranking innovation. The previ

Meta continues to lead the industry in utilizing groundbreaking AI Recommendation Systems (RecSys) to deliver better experiences for people, and better results

Meta is continuing its long-term roadmap to help the construction industry leverage AI to produce high-quality and more sustainable concrete mixes, as well as t

Friend bubbles in Facebook Reels highlight Reels your friends have liked or reacted to, helping you discover new content and making it easier to connect over sh

Meta’s Ranking Engineer Agent (REA) autonomously executes key steps across the end-to-end machine learning (ML) lifecycle for ads ranking models. This post cove

Even seemingly simple engineering tasks — like updating an API — can become monumental undertakings when you’re dealing with millions of lines of code and thous

We’re sharing the technical details behind how Advanced Browsing Protection (ABP) in Messenger protects the privacy of the links clicked on within chats while s

FFmpeg is truly a multi-tool for media processing. As an industry-standard tool it supports a wide variety of audio and video codecs and container formats. It c

Meta recognizes the long-term benefits of jemalloc, a high-performance memory allocator, in its software infrastructure. We are renewing focus on jemalloc, aimi

We are open-sourcing the initial version of RCCLX – an enhanced version of RCCL that we developed and tested on Meta’s internal workloads. RCCLX is fully integr