About this role
Meta is building the next generation of wearable devices that bring people closer together. As a Software Engineer on the Wearables Interfaces Engineering team, you will be responsible for the platform-level software that bridges Core OS capabilities with the application and experience layers on Meta's wearable devices. You will drive cross-functional system design decisions, own the most complex multi-component technical challenges, and help set the technical direction for how platform software leverages Core OS to deliver immersive user experiences. This role requires deep systems thinking across firmware, OS interfaces, frameworks, middleware, and applications—and the ability to lead major initiatives that span organizational boundaries.
Responsibilities
Drive platform software architecture for wearable devices, ensuring coherent integration across Core OS interfaces, frameworks, middleware, and application layers
Lead system-level initiatives that span OS-to-application boundaries, optimizing frameworks, system services, and applications for performance, reliability, and power efficiency
Own resolution of the most complex, ambiguous technical problems that span multiple components—OS interfaces, drivers, frameworks, and application software—identifying root causes and driving fixes across teams
Analyze and optimize platform-level performance, latency, memory usage, and power consumption across the full stack, setting org-wide standards and tooling for measurement
Partner with the Core OS team to define platform requirements, influence OS roadmaps, and ensure platform needs are met by underlying system capabilities
Establish metrics, monitoring, and reliability frameworks to maintain system health for platform software across the wearables portfolio
Collaborate cross-functionally with Core OS, hardware, firmware, connectivity, multimedia, and product teams to align technical strategies and unblock dependencies
Communicate platform architecture decisions, integration strategies, and technical trade-offs clearly to stakeholders at all levels, driving alignment on direction and priorities
Leverage AI tools and workflows to accelerate development, improve system analysis, and scale your impact across the organization
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
10+ years of experience in systems engineering, platform software, or embedded systems development
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience
Experience leading complex platform integration efforts across OS, frameworks, and application teams with demonstrated org-level impact
Expert-level understanding of platform architecture including interactions between OS (Linux/Android), system services, frameworks, and application software
Proficiency in C/C++ and/or Java/Kotlin with experience debugging across multiple layers of the stack
Experience with system-level debugging tools and methodologies (system traces, performance profilers, memory analyzers)
Track record of solving highly complex technical problems that span multiple systems and teams
Experience shipping consumer electronics or embedded devices at scale
Understanding of power management, thermal constraints, and performance optimization at the platform level Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Background in sensor systems, connectivity (BT/WiFi/Cellular), multimedia, or neural interfaces at the platform layer
Experience using AI-powered tools to optimize engineering workflows and drive measurable efficiency gains
Experience with Android platform internals, system services, or framework-level software
Familiarity with hardware interfaces and how they surface through OS/driver layers to platform software
Track record of leading large-scale projects from concept through mass production
Experience working with Core OS teams to define requirements and influence OS capabilities
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience with wearable devices, AR/VR systems, or mobile device platforms
Proficiency in scripting languages (Python, Shell) for system automation and analysis
