Engineering at Meta
- Meta Open Source: 2024 by the numbers
- Mobile GraphQL at Meta in 2025
- Building multimodal AI for Ray-Ban Meta glasses
- A case for QLC SSDs in the data center
- How Meta is translating its Java codebase to Kotlin
- Protecting user data through source code analysis at scale
- Unlocking global AI potential with next-generation subsea infrastructure
- Looking back at our Bug Bounty program in 2024
- Revolutionizing software testing: Introducing LLM-powered bug catchers
- Data logs: The latest evolution in Meta’s access tools
- How Precision Time Protocol handles leap seconds
- Bringing Jetpack Compose to Instagram for Android
- How Meta discovers data flows via lineage at scale
- Strobelight: A profiling service built on open source technology
- Powering AI innovation by acccelerating the next wave of nuclear
- Meta Andromeda: Supercharging Advantage+ automation with the next-gen personalized ads retrieval engine
- Sequence learning: A paradigm shift for personalized ads recommendations
- How Meta built large-scale cryptographic monitoring
- Diff Authoring Time: Measuring developer productivity at Meta
- IPLS: Privacy-preserving storage for your WhatsApp contacts
- OCP Summit 2024: The open future of networking hardware for AI
- Meta’s open AI hardware vision
- How open source AI can improve population estimates, sustainable energy, and the delivery of climate change interventions
- React at Meta Connect 2024
- Inside Bento: Jupyter Notebooks at Meta
- Simulator-based reinforcement learning for data center cooling optimization
- Read Meta’s 2024 Sustainability Report
- Meta is getting ready for post-quantum cryptography
- How Meta enforces purpose limitation via Privacy Aware Infrastructure at scale
- RETINAS: Real-Time Infrastructure Accounting for Sustainability
- How PyTorch powers AI training and inference
- Inside the hardware and co-design of MTIA
- Bringing Llama 3 to life
- Aparna Ramani discusses the future of AI infrastructure
- How Meta animates AI-generated images at scale
- A RoCE network for distributed AI training at scale
- DCPerf: An open source benchmark suite for hyperscale compute applications
- Meet Caddy – Meta’s next-gen mixed reality CAD software
- AI Lab: The secrets to keeping machine learning engineers moving fast
- Taming the tail utilization of ads inference at Meta scale
- Meta’s approach to machine learning prediction robustness
- The key to a happy Rust/C++ relationship
- Leveraging AI for efficient incident response
- PVF: A novel metric for understanding AI systems’ vulnerability against SDCs in model parameters
- MLow: Meta’s low bitrate audio codec
- How Meta trains large language models at scale
- Maintaining large-scale AI capacity at Meta
- Unlocking the power of mixed reality devices with MobileConfig
- Serverless Jupyter Notebooks at Meta
- Composable data management at Meta
- Post-quantum readiness for TLS at Meta
- Behind the scenes of Threads for web
- Building new custom silicon for Meta’s AI workloads
- Building an infrastructure for AI’s future
- Introducing the next-gen Meta Training and Inference Accelerator
- Bringing HDR photo support to Instagram and Threads
- Threads has entered the fediverse
- Optimizing RTC bandwidth estimation with machine learning