Embedded Software Engineer

Meta is seeking an Embedded Software Engineer to drive the technical direction of low-level software systems powering Meta's next generation of wearable and consumer hardware devices. In this role, you will lead a team of engineers focused on device factory software development, ensuring seamless integration between manufacturing processes and embedded systems. You will work closely with internal engineering leads as well as external partners including vendors and factory stakeholders to align on requirements, timelines, and quality standards. You will architect and deliver embedded software solutions spanning firmware, real-time operating systems, hardware abstraction layers, and system services, collaborating closely with hardware, silicon, and product teams to bring innovative wearable experiences to life at scale.

Responsibilities

Architect and lead the development of embedded software components including firmware, BSP, hardware abstraction layers, and real-time OS services for wearable and consumer hardware platforms Own the technical design of embedded subsystems, evaluating trade-offs across power consumption, latency, memory footprint, and hardware integration constraints Drive the embedded software roadmap for one or more product areas, obtaining alignment from hardware, silicon, and cross-functional engineering stakeholders Establish and enforce coding standards, testing frameworks, and rollout practices specific to embedded and firmware development across the team Instrument and profile embedded systems to identify performance bottlenecks, optimize critical code paths, and define service level objectives for system reliability Lead root cause analysis of complex firmware defects and system-level failures, including non-reproducible issues in multithreaded or interrupt-driven environments Collaborate with hardware and electrical engineering teams during bring-up, validation, and integration of new silicon and peripheral components Mentor other engineers on embedded systems best practices, including safe memory management, real-time scheduling, and hardware-software co-design Contribute to recruiting efforts by conducting technical interviews and articulating the embedded systems product vision to attract experienced candidates Proactively identify and reduce technical debt in embedded codebases, driving migrations and tooling improvements that increase development velocity across the team

Qualifications

6+ years of experience in embedded software development 2+ years of experience working as a tech lead role driving all engineering activities of a team Experience programming in C and C++ for resource-constrained embedded targets, including memory management, interrupt handling, and low-level peripheral drivers Experience leading the technical design and delivery of major embedded software initiatives across cross-functional hardware and software teams Experience debugging complex embedded system issues using tools such as JTAG debuggers, logic analyzers, oscilloscopes, or static analysis frameworks Experience defining and tracking reliability and performance metrics for embedded systems, including power, latency, and memory utilization Experience with wearable, AR, or device hardware platforms, including sensor fusion, wireless communication stacks, or low-power system design Professional working proficiency in English and Mandarin, as the role requires collaboration with engineering teams and manufacturing partners in Mandarin-speaking regions Experience with hardware bring-up and board support package development for custom silicon or system-on-chip designs 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/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience applying AI-assisted development tools to accelerate embedded software workflows, including automated testing, code generation, or anomaly detection in system telemetry Experience with embedded Linux, RTOS platforms such as FreeRTOS or Zephyr, or custom bare-metal firmware architectures Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies