Job description

Meta is building the next generation of intelligent devices powered by custom silicon and deeply integrated cloud services. As a Staff Software Engineer on this team, you will own the end-to-end software architecture that spans Meta's custom SoC platform, on-device AOSP-based software, and the backend services that extend device capabilities into the cloud. You will drive the most complex cross-boundary technical decisions—bridging low-level hardware abstraction, Android platform software, and scalable backend infrastructure—to deliver seamless, high-performance experiences. This role demands deep expertise across embedded/on-device systems and distributed backend services, and the ability to lead major initiatives that require tight coordination between silicon, device software, and cloud teams. Define and drive the end-to-end system architecture spanning on-device software (AOSP, Meta custom SoC interfaces) and Meta's backend services, ensuring coherent data flow, low latency, and reliability across the full stack Lead the design and implementation of platform software that leverages Meta's custom SoC capabilities—including hardware accelerators, DSPs, and specialized compute units—through AOSP system services, HALs, and native frameworks Own resolution of the most complex, ambiguous technical problems that cross the device–cloud boundary: diagnosing issues that manifest across silicon bring-up, OS layers, network transport, and backend service interactions Architect backend services that support on-device workloads—including model serving, telemetry pipelines, OTA update infrastructure, device management, and cloud offload—optimizing for scale, availability, and cost efficiency Drive performance optimization across the full stack: silicon-aware scheduling on-device, efficient serialization and transport protocols, and backend service latency/throughput at scale Partner with silicon/hardware teams to define software requirements for Meta's custom SoC, influence silicon roadmaps, and ensure platform software fully exploits custom hardware capabilities Establish system-level metrics, monitoring, and reliability frameworks that provide end-to-end observability from on-device health through backend service SLAs Collaborate cross-functionally with silicon, firmware, OS platform, product, ML/AI, and infrastructure teams to align technical strategies, unblock dependencies, and drive org-level outcomes Communicate architecture decisions, integration strategies, and technical trade-offs to stakeholders at all levels—driving alignment across device and backend organizations Leverage AI tools and workflows to accelerate development, improve system analysis, and scale your impact across the organization Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 10+ years of experience in systems software engineering, with significant depth in both on-device/embedded platforms and backend/distributed systems Experience leading complex initiatives that span hardware–software–cloud boundaries with demonstrated org-level impact Deep understanding of Android platform internals (AOSP): system services, HAL interfaces, native frameworks, and build/integration workflows Strong proficiency in C/C++ for on-device systems programming and Java/Kotlin or Python/C++ for backend service development Experience working with custom silicon or SoC platforms—including hardware bring-up, driver integration, or hardware abstraction layer development Experience designing and operating large-scale backend services (e.g., RPC frameworks, data pipelines, model serving, distributed storage) Track record of solving highly complex technical problems that span multiple systems, teams, and organizational boundaries Experience with system-level debugging across the full stack: hardware traces, OS-level profiling, network diagnostics, and backend service observability Experience shipping consumer devices or embedded systems at scale alongside their supporting cloud infrastructure Experience with large-scale backend infrastructure (RPC frameworks, distributed data stores, real-time analytics) or equivalent service frameworks Familiarity with custom silicon workflows: firmware/software co-design, DSP programming, hardware accelerator integration, or silicon validation Experience with on-device ML inference, model optimization (quantization, compilation for custom accelerators), and cloud-to-device model deployment pipelines Proficiency in power-aware software design: balancing on-device compute vs. cloud offload for battery life, thermal, and latency constraints Experience with OTA systems, device fleet management, or A/B experimentation frameworks for hardware products Background in real-time or low-latency systems: sensor fusion, streaming media, or interactive workloads that span device and cloud Experience with wearable devices, AR/VR systems, mobile platforms, or IoT at scale Track record of leading large-scale projects from silicon bring-up through mass production and live service operation Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize engineering workflows and drive measurable efficiency gains Experience defining APIs and contracts between on-device and backend systems that remain stable across hardware generations

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Platform: meta
Effort: medium