Meta runs social platforms and is pushing into AI, VR and wearables, but its job posts lean heavily on physical infrastructure: Procore, Autodesk BIM 360, Bluebeam and CMMS sit alongside PyTorch and Kubernetes. Recurring pain points around data center uptime, BMS reliability and schedule risk show a large capital buildout underway. Adoption of Llama, Kubeflow and Docker points to expanding in-house ML training at scale, while overall hiring is decelerating and skews senior.
Notable leadership hires: Media Director, Art Director, Area Schedule Lead, Environmental Health Safety Lead, Media Lead
Meta is a public company headquartered in Menlo Park, CA, with more than 10,000 employees. It operates social and messaging apps including Facebook, Messenger, Instagram and WhatsApp, and is investing in virtual reality, augmented reality, wearables and artificial intelligence. Its engineering stack spans Python, C++, PHP, Rust, Go, Java and MySQL, with PyTorch and TensorFlow for machine learning. The company also runs a global network and data center operation and recruits across the United States, United Kingdom, India, Singapore, China, the UAE, Israel, France and South Korea.
Meta's stack includes Python, C++, PHP, Rust, Go, Java, MySQL, PyTorch, TensorFlow, Kubernetes and Terraform, plus Procore, Autodesk BIM 360 and CMMS for data center construction and operations.
Meta is adopting Llama, GPT, Falcon, Core ML, Kubeflow, Kubernetes and Docker, and its projects include low-level kernels for ML training and hardware-software co-design.
Meta hires in the United States, United Kingdom, India, Singapore, China, United Arab Emirates, Israel, France and South Korea, with an engineering- and operations-heavy, senior-skewed mix.
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Meta's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.