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.
Responsibilities
- 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
Minimum Qualifications
- 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